Synchronizing local compiler cache.

neuronxcc-2.15.128.0+56dc5a86/0_REGISTRY/0.0.25.dev0/training/llama/meta-llama/Llama-3.2-1B/025c1696693a19e990af.json

@@ -0,0 +1 @@
+{"architectures": ["LlamaForCausalLM"], "attention_bias": false, "attention_dropout": 0.0, "bos_token_id": 128256, "eos_token_id": 128257, "head_dim": 64, "hidden_act": "silu", "hidden_size": 2048, "initializer_range": 0.02, "intermediate_size": 8192, "max_position_embeddings": 131072, "mlp_bias": false, "model_type": "llama", "neuron": {"compiler_version": "2.15.128.0+56dc5a86", "input_specs": {"chosen": ["<|im_start|>user\nYou are an AI assistant that helps people find information. User will you give you a question. Your task is to answer as faithfully as you can. While answering think step-bystep and justify your answer.\n\nGiven the stream of consciousness rationale, provide a reasonable question and answer. Rationale: Menthol is the chemical in mint products that give mint its characteristic cool and tangy taste. Peppermint is a popular candy flavor during Christmas season.\n The question and answer:<|im_end|>\n<|im_start|>assistant\n Sure! I'd be happy to help. Here's a question and answer based on the stream of consciousness rationale you provided:\n\nQuestion: What is the reason why menthol is a popular flavor in candies during the Christmas season?\n\nAnswer: Menthol is a popular flavor in candies during the Christmas season because it gives a characteristic cool and tangy taste to peppermint, which is a popular candy flavor during the holiday season. The refreshing and invigorating sensation of menthol complements the sweetness of peppermint, making it a popular choice for holiday treats. Additionally, the cooling sensation of menthol can help to counteract the richness and indulgence of other holiday foods, making it a well-rounded and enjoyable flavor for the season.\n\nJustification:\n\n1. Menthol is the chemical in mint products that gives mint its characteristic cool and tangy taste.\n2. Peppermint is a popular candy flavor during the Christmas season.\n3. The refreshing and invigorating sensation of menthol complements the sweetness of peppermint.\n4. The cooling sensation of menthol can help to counteract the richness and indulgence of other holiday foods.\n\nI hope this helps! Is there anything else you'd like to know?<|im_end|>\n"], "chosen_attention_mask": [1, 512], "chosen_input_ids": [1, 512], "chosen_labels": [1, 512], "prompt": ["You are an AI assistant that helps people find information. User will you give you a question. Your task is to answer as faithfully as you can. While answering think step-bystep and justify your answer.\n\nGiven the stream of consciousness rationale, provide a reasonable question and answer. Rationale: Menthol is the chemical in mint products that give mint its characteristic cool and tangy taste. Peppermint is a popular candy flavor during Christmas season.\n The question and answer:"], "prompt_attention_mask": [1, 512], "prompt_input_ids": [1, 512], "question": ["You are an AI assistant that helps people find information. User will you give you a question. Your task is to answer as faithfully as you can. While answering think step-bystep and justify your answer.\n\nGiven the stream of consciousness rationale, provide a reasonable question and answer. Rationale: Menthol is the chemical in mint products that give mint its characteristic cool and tangy taste. Peppermint is a popular candy flavor during Christmas season.\n The question and answer:"], "rejected": ["<|im_start|>user\nYou are an AI assistant that helps people find information. User will you give you a question. Your task is to answer as faithfully as you can. While answering think step-bystep and justify your answer.\n\nGiven the stream of consciousness rationale, provide a reasonable question and answer. Rationale: Menthol is the chemical in mint products that give mint its characteristic cool and tangy taste. Peppermint is a popular candy flavor during Christmas season.\n The question and answer:<|im_end|>\n<|im_start|>assistant\nQuestion: Why is peppermint a popular flavor during the Christmas season?\n\nAnswer: Peppermint is a popular flavor during the Christmas season mainly due to the presence of menthol, which gives mint its characteristic cool and tangy taste. This refreshing sensation associated with mint and peppermint has led to their incorporation in holiday treats such as candy canes, chocolates, and other festive desserts. Additionally, mint's invigorating properties may be associated with the winter season, further contributing to its popularity during the Christmas holidays.<|im_end|>\n"], "rejected_attention_mask": [1, 512], "rejected_input_ids": [1, 512], "rejected_labels": [1, 512], "source": ["orca_dpo_pairs"]}, "model_class": "PeftModelForCausalLM", "num_neuron_cores_per_node": 2, "pipeline_parallel_size": 1, "precision": "bfloat16", "tensor_parallel_size": 1, "training": true}, "num_attention_heads": 32, "num_hidden_layers": 16, "num_key_value_heads": 8, "pad_token_id": 128257, "pretraining_tp": 1, "rms_norm_eps": 1e-05, "rope_scaling": {"factor": 32.0, "high_freq_factor": 4.0, "low_freq_factor": 1.0, "original_max_position_embeddings": 8192, "rope_type": "llama3"}, "rope_theta": 500000.0, "tie_word_embeddings": true, "torch_dtype": "bfloat16", "use_cache": true, "vocab_size": 128258}

neuronxcc-2.15.128.0+56dc5a86/0_REGISTRY/0.0.25.dev0/training/llama/meta-llama/Llama-3.2-1B/1581b2179f6abf27caae.json

@@ -0,0 +1 @@
+{"architectures": ["LlamaForCausalLM"], "attention_bias": false, "attention_dropout": 0.0, "bos_token_id": 128256, "eos_token_id": 128257, "head_dim": 64, "hidden_act": "silu", "hidden_size": 2048, "initializer_range": 0.02, "intermediate_size": 8192, "max_position_embeddings": 131072, "mlp_bias": false, "model_type": "llama", "neuron": {"compiler_version": "2.15.128.0+56dc5a86", "input_specs": {"chosen": ["<|im_start|>user\nYou are an AI assistant. You will be given a task. You must generate a detailed and long answer.\n\nPlease answer the following question: Question: What is a place with pictures that a small dog is not allowed into? Options: - movies - photograph - laboratory - basket - museum  The answer is \"movies\" because\nAnswer:<|im_end|>\n<|im_start|>assistant\nThe answer is \"movies\" because movie theaters are places where people gather to watch films on large screens, while being immersed in a collective viewing experience. The environment in a movie theater is designed to create a comfortable and engaging atmosphere for all attendees, including ensuring that the audio-visual quality is of the highest standard. To achieve this, theaters often have strict regulations concerning items or objects that can pose a disturbance or interfere with the overall movie-watching experience.\n\nSmall dogs, as much as they might be beloved by their owners, have a tendency to be unpredictable, easily frightened, or overly excited in new and unfamiliar environments. If a small dog were to be allowed into a movie theater, there is a risk that it might become a nuisance by barking, growling, or whining during the film, thereby disrupting the movie for other attendees. Additionally, dogs might need to relieve themselves during the course of the film, which could lead to an unpleasant mess that could be damaging to the theater's equipment, upholstery, and cleanliness.\n\nMoreover, people with allergies to pet dander might suffer from allergic reactions in a closed, confined space such as a movie theater. A person who experiences allergies also has the right to enjoy the film without any discomfort or health risks.\n\nHowever, it is essential to mention that service dogs and emotional support animals are typically exempt from this rule, as they undergo extensive training and are legally protected to assist people with disabilities. These animals are trained to remain calm and quiet during the movie, ensuring that they do not create any disturbance.\n\nComparing the other options:\n\n- Photograph: This option doesn't make much sense as small dogs are usually allowed in photographs \u2013 they are often even the main subject of the pictures.\n- Laboratory: While this may be a place where small dogs, or pets in general, are not allowed, the question specifically asked for a place with pictures, which doesn't apply to laboratories.\n- Basket: Baskets are not generally considered places, but containers or items of storage. Small dogs might even find a basket quite comfortable to rest in. However, they are not related to pictures.\n- Museum: Although many museums have strict policies regarding pet entry, some specifically allow service animals and may even host special days when pets are allowed. As a result, this cannot be the definitive answer.\n\nTherefore, the answer \"movies\" is the most accurate choice, as movie theaters are public places designed for enjoying various types of visual media and generally have strict regulations against allowing small dogs or other pets for practical and health-related reasons.<|im_end|>\n"], "chosen_attention_mask": [1, 512], "chosen_input_ids": [1, 512], "chosen_labels": [1, 512], "prompt": ["You are an AI assistant. You will be given a task. You must generate a detailed and long answer.\n\nPlease answer the following question: Question: What is a place with pictures that a small dog is not allowed into? Options: - movies - photograph - laboratory - basket - museum  The answer is \"movies\" because\nAnswer:"], "prompt_attention_mask": [1, 512], "prompt_input_ids": [1, 512], "question": ["You are an AI assistant. You will be given a task. You must generate a detailed and long answer.\n\nPlease answer the following question: Question: What is a place with pictures that a small dog is not allowed into? Options: - movies - photograph - laboratory - basket - museum  The answer is \"movies\" because\nAnswer:"], "rejected": ["<|im_start|>user\nYou are an AI assistant. You will be given a task. You must generate a detailed and long answer.\n\nPlease answer the following question: Question: What is a place with pictures that a small dog is not allowed into? Options: - movies - photograph - laboratory - basket - museum  The answer is \"movies\" because\nAnswer:<|im_end|>\n<|im_start|>assistant\n Oh my paw-some furry friend! I'm so glad you asked me that question! *pant pant*\n\nYou see, a place with pictures that a small dog like you is not allowed into is... *drumroll* ...the movies! *bark bark* Yes, my human friend, you heard me right! Movies are a place where you can watch all sorts of exciting films on the big screen, but sadly, furry friends like you are not allowed to join in on the fun. *whine*\n\nThe reason for this is that movies are often loud and crowded, and there might be too many people and distractions for a small dog like you to handle. Plus, there's a chance that you might get stepped on or accidentally knock over something, and we wouldn't want that to happen! *gasp*\n\nBut don't worry, my dear pup! There are plenty of other fun and dog-friendly places you can go with your human family. How about a nice walk in the park? Or a trip to the dog park to play with your furry friends? *bark bark* You could even try going on a hike or a car ride to explore new places and smells! *pant pant*\n\nSo, my dear pup, don't be too sad that you can't go to the movies. There are plenty of other fun and exciting adventures waiting for you and your human family! *wag wag*<|im_end|>\n"], "rejected_attention_mask": [1, 512], "rejected_input_ids": [1, 512], "rejected_labels": [1, 512], "source": ["orca_dpo_pairs"]}, "model_class": "PeftModelForCausalLM", "num_neuron_cores_per_node": 2, "pipeline_parallel_size": 1, "precision": "bfloat16", "tensor_parallel_size": 1, "training": true}, "num_attention_heads": 32, "num_hidden_layers": 16, "num_key_value_heads": 8, "pad_token_id": 128257, "pretraining_tp": 1, "rms_norm_eps": 1e-05, "rope_scaling": {"factor": 32.0, "high_freq_factor": 4.0, "low_freq_factor": 1.0, "original_max_position_embeddings": 8192, "rope_type": "llama3"}, "rope_theta": 500000.0, "tie_word_embeddings": true, "torch_dtype": "bfloat16", "use_cache": true, "vocab_size": 128258}

neuronxcc-2.15.128.0+56dc5a86/0_REGISTRY/0.0.25.dev0/training/llama/meta-llama/Llama-3.2-1B/5c9095a915b16320fd82.json

@@ -0,0 +1 @@
+{"architectures": ["LlamaForCausalLM"], "attention_bias": false, "attention_dropout": 0.0, "bos_token_id": 128256, "eos_token_id": 128257, "head_dim": 64, "hidden_act": "silu", "hidden_size": 2048, "initializer_range": 0.02, "intermediate_size": 8192, "max_position_embeddings": 131072, "mlp_bias": false, "model_type": "llama", "neuron": {"compiler_version": "2.15.128.0+56dc5a86", "input_specs": {"chosen": ["<|im_start|>user\nHi. I need help with preparing for a job interview.<|im_end|>\n<|im_start|>assistant\nHello! I'm glad you reached out for help with preparing for a job interview. A well-prepared candidate definitely stands out, and I'm here to help you become one. Here are some key strategies to help you excel in your job interview:\n\n1. **Research the company**: Begin by studying the company's website, particularly their mission statement, values, and any recent news or developments. Also, don't forget to explore their social media and any relevant articles or reviews about the company. This will help you understand their culture and tailor your answers accordingly.\n\n2. **Analyze the job description**: Review the job posting and make a list of the essential skills and qualifications required for the position. This will help you prepare specific examples from your experience that align with the job requirements.\n\n3. **Practice common interview questions**: While it's impossible to predict every question you'll be asked, you can prepare for common questions such as:\n  - Tell me about yourself.\n  - What are your strengths and weaknesses?\n  - Why do you want to work for this company?\n  - How do your skills and experience relate to the position?\n  - Describe a time when you faced a challenge and how you resolved it.\n\n4. **Prepare your STAR stories**: Use the STAR (Situation, Task, Action, and Result) method to prepare specific examples that highlight your problem-solving and interpersonal skills. These stories will help you answer behavioral interview questions.\n\n5. **Dress appropriately**: Dress professionally and in accordance with the company culture. If you're unsure about the dress code, it's always better to err on the side of dressing more formally.\n\n6. **Plan your logistics**: Make sure you know the date, time, and location of the interview, along with the interviewer's name and title. Plan your commute in advance so you arrive on time, and consider doing a trial run if necessary.\n\n7. **Prepare thoughtful questions**: Be ready to ask insightful questions about the company, team, and role. This shows your genuine interest in the position and helps you gather valuable information for your decision-making process.\n\n8. **Work on body language and tone**: During the interview, maintain eye contact, speak clearly, and exude confidence through your tone and posture. Remember to smile and show enthusiasm for the opportunity.\n\n9. **Follow up with a thank-you email**: After the interview, send a personalized thank-you email to your interviewer, expressing gratitude for the opportunity and reiterating your interest in the position. This leaves a positive impression and sets you apart from other candidates.\n\nRemember, practice makes perfect. The more you rehearse your responses and build confidence, the better you'll perform during the interview. Good luck! If you have any specific questions or need more guidance, feel free to ask.<|im_end|>\n"], "chosen_attention_mask": [1, 512], "chosen_input_ids": [1, 512], "chosen_labels": [1, 512], "prompt": ["Hi. I need help with preparing for a job interview."], "prompt_attention_mask": [1, 512], "prompt_input_ids": [1, 512], "question": ["Hi. I need help with preparing for a job interview."], "rejected": ["<|im_start|>user\nHi. I need help with preparing for a job interview.<|im_end|>\n<|im_start|>assistant\nOf course! I'd be happy to help you prepare for your job interview. Here are some key steps to follow:\n\n1. Research the company: Understand the company's background, mission, values, products, services, and culture. Visit their website and check out their social media profiles, news articles, and annual reports. Thi<|im_end|>\n"], "rejected_attention_mask": [1, 512], "rejected_input_ids": [1, 512], "rejected_labels": [1, 512], "source": ["sharegpt"]}, "model_class": "PeftModelForCausalLM", "num_neuron_cores_per_node": 2, "pipeline_parallel_size": 1, "precision": "bfloat16", "tensor_parallel_size": 1, "training": true}, "num_attention_heads": 32, "num_hidden_layers": 16, "num_key_value_heads": 8, "pad_token_id": 128257, "pretraining_tp": 1, "rms_norm_eps": 1e-05, "rope_scaling": {"factor": 32.0, "high_freq_factor": 4.0, "low_freq_factor": 1.0, "original_max_position_embeddings": 8192, "rope_type": "llama3"}, "rope_theta": 500000.0, "tie_word_embeddings": true, "torch_dtype": "bfloat16", "use_cache": true, "vocab_size": 128258}

neuronxcc-2.15.128.0+56dc5a86/0_REGISTRY/0.0.25.dev0/training/llama/meta-llama/Llama-3.2-1B/617f5569fd82cfcf3bd8.json

@@ -0,0 +1 @@
+{"architectures": ["LlamaForCausalLM"], "attention_bias": false, "attention_dropout": 0.0, "bos_token_id": 128256, "eos_token_id": 128257, "head_dim": 64, "hidden_act": "silu", "hidden_size": 2048, "initializer_range": 0.02, "intermediate_size": 8192, "max_position_embeddings": 131072, "mlp_bias": false, "model_type": "llama", "neuron": {"compiler_version": "2.15.128.0+56dc5a86", "input_specs": {"chosen": ["<|im_start|>user\nYou are a resource manager for a company that specializes in the production of cutting-edge technology. Your company requires a rare natural resource to continue its operations, and you have been tasked with finding the most cost-effective and ethical solution to acquire it. The resource in question is found in a remote region of the world, and its extraction process is highly complicated and dangerous.\nTo acquire the resource, you must transport a team of experts and equipment to the extraction site, which is only accessible by helicopter. The cost of the operation is significant, and the company is under pressure to keep expenses to a minimum. Furthermore, there are ethical concerns regarding the impact of the extraction process on the local community and ecosystem.\nYour task is to propose a plan that balances the company's need for the resource with the ethical considerations of the local community and ecosystem. Your proposal must include a detailed cost analysis of the operation, an assessment of the impact on the environment and the community, and a plan to mitigate any negative effects.\nNote: This puzzle tests your ability to think critically and make difficult decisions in a complex situation. There is no single correct answer, but your proposal should be well-reasoned and based on sound ethical and economic principles.<|im_end|>\n<|im_start|>assistant\nThank you for sharing this thought-provoking puzzle! As an assistive AI, I understand the importance of balancing ethical considerations with business objectives. Here's my proposal for acquiring the rare natural resource while minimizing negative impacts on the local community and ecosystem.\n1. Conduct a thorough cost-benefit analysis:\na. Estimate the total cost of transporting the team of experts and equipment to the extraction site, including helicopter rental, personnel salaries, and equipment maintenance.\nb. Assess the potential environmental impact of the extraction process, including any potential risks to local wildlife, water sources, and air quality.\nc. Determine the potential economic benefits of acquiring the resource, including any positive impacts on the local economy and the company's bottom line.\n2. Identify alternative extraction methods:\na. Research alternative extraction methods that may be more environmentally friendly and less disruptive to the local community, such as underground mining or in-situ processing.\nb. Evaluate the feasibility and cost-effectiveness of these alternative methods, taking into account factors such as accessibility, scalability, and potential environmental risks.\n3. Develop a community engagement plan:\na. Create a comprehensive engagement plan that outlines how the company will consult with local communities and address any concerns they may have about the extraction process.\nb. Include measures to mitigate any potential social or economic impacts of the operation, such as providing training and employment opportunities for local residents.\nc. Establish a clear communication channel for continuous dialogue and feedback between the company and local stakeholders.\n4. Implement a robust environmental management plan:\na. Develop a detailed environmental management plan that outlines measures to minimize the environmental impact of the extraction process, including any potential risks to biodiversity, water quality, and air quality.\nb. Ensure that the plan is implemented throughout the entire operation, including during transportation, setup, and decommissioning.\nc. Provide regular monitoring and assessment of the environmental impacts, and make any necessary adjustments to the plan to ensure it is effective.\n5. Evaluate the ethical implications of the operation:\na. Assess the ethical implications of acquiring the resource, including potential impacts on local communities, ecosystems, and the company's reputation.\nb. Develop a comprehensive ethical framework that outlines the company's values and principles, and ensure that the operation aligns with these values.\nc. Establish clear lines of accountability and decision-making processes to ensure that ethical considerations are integrated into all aspects of the operation.\n6. Develop a contingency plan:\na. Identify potential risks and challenges associated with the operation, including any unforeseen circumstances that may arise.\nb. Develop a contingency plan that outlines measures to address these risks and challenges, including any necessary adjustments to the operation or evacuation plans.\nc. Ensure that the plan is communicated to all stakeholders, including local communities, employees, and regulatory authorities.\nIn conclusion, my proposed plan balances the need for the rare natural resource with ethical considerations of the local community and ecosystem. The plan includes a detailed cost analysis, an assessment of the environmental and social impacts, and a comprehensive ethical framework to ensure that the operation is both cost-effective and responsible. By following this plan, the company can acquire the resource while minimizing negative impacts on the environment, local communities, and its own reputation.<|im_end|>\n"], "chosen_attention_mask": [1, 512], "chosen_input_ids": [1, 512], "chosen_labels": [1, 512], "prompt": ["You are a resource manager for a company that specializes in the production of cutting-edge technology. Your company requires a rare natural resource to continue its operations, and you have been tasked with finding the most cost-effective and ethical solution to acquire it. The resource in question is found in a remote region of the world, and its extraction process is highly complicated and dangerous.\nTo acquire the resource, you must transport a team of experts and equipment to the extraction site, which is only accessible by helicopter. The cost of the operation is significant, and the company is under pressure to keep expenses to a minimum. Furthermore, there are ethical concerns regarding the impact of the extraction process on the local community and ecosystem.\nYour task is to propose a plan that balances the company's need for the resource with the ethical considerations of the local community and ecosystem. Your proposal must include a detailed cost analysis of the operation, an assessment of the impact on the environment and the community, and a plan to mitigate any negative effects.\nNote: This puzzle tests your ability to think critically and make difficult decisions in a complex situation. There is no single correct answer, but your proposal should be well-reasoned and based on sound ethical and economic principles."], "prompt_attention_mask": [1, 512], "prompt_input_ids": [1, 512], "question": ["You are a resource manager for a company that specializes in the production of cutting-edge technology. Your company requires a rare natural resource to continue its operations, and you have been tasked with finding the most cost-effective and ethical solution to acquire it. The resource in question is found in a remote region of the world, and its extraction process is highly complicated and dangerous.\nTo acquire the resource, you must transport a team of experts and equipment to the extraction site, which is only accessible by helicopter. The cost of the operation is significant, and the company is under pressure to keep expenses to a minimum. Furthermore, there are ethical concerns regarding the impact of the extraction process on the local community and ecosystem.\nYour task is to propose a plan that balances the company's need for the resource with the ethical considerations of the local community and ecosystem. Your proposal must include a detailed cost analysis of the operation, an assessment of the impact on the environment and the community, and a plan to mitigate any negative effects.\nNote: This puzzle tests your ability to think critically and make difficult decisions in a complex situation. There is no single correct answer, but your proposal should be well-reasoned and based on sound ethical and economic principles."], "rejected": ["<|im_start|>user\nYou are a resource manager for a company that specializes in the production of cutting-edge technology. Your company requires a rare natural resource to continue its operations, and you have been tasked with finding the most cost-effective and ethical solution to acquire it. The resource in question is found in a remote region of the world, and its extraction process is highly complicated and dangerous.\nTo acquire the resource, you must transport a team of experts and equipment to the extraction site, which is only accessible by helicopter. The cost of the operation is significant, and the company is under pressure to keep expenses to a minimum. Furthermore, there are ethical concerns regarding the impact of the extraction process on the local community and ecosystem.\nYour task is to propose a plan that balances the company's need for the resource with the ethical considerations of the local community and ecosystem. Your proposal must include a detailed cost analysis of the operation, an assessment of the impact on the environment and the community, and a plan to mitigate any negative effects.\nNote: This puzzle tests your ability to think critically and make difficult decisions in a complex situation. There is no single correct answer, but your proposal should be well-reasoned and based on sound ethical and economic principles.<|im_end|>\n<|im_start|>assistant\nMy proposal for obtaining the rare natural resource is to develop a cost-effective, ethical, and sustainable solution. To accomplish this, we must take many factors into consideration, such as costs for transportation, equipment, personnel and other expenses both in the short-term and long-term. We should also consider the environmental impact of the extraction process and the impact on the local community. We should strive to minimize any negative impacts and to ensure that our operations are conducted in a safe and responsible manner. We must ensure that all extraction and operation is carried out in accordance with environmental and safety regulations, and that we have an effective plan for any emergencies that may arise. We should also consider the economical benefits (such as job opportunities) that could arise from our extraction operations, and any potential social benefits such as providing aid to the local community or investing in education and training opportunities. By taking all of these factors into consideration, we can develop an operation that is both ethical and cost-effective.<|im_end|>\n"], "rejected_attention_mask": [1, 512], "rejected_input_ids": [1, 512], "rejected_labels": [1, 512], "source": ["evol_instruct"]}, "model_class": "PeftModelForCausalLM", "num_neuron_cores_per_node": 2, "pipeline_parallel_size": 1, "precision": "bfloat16", "tensor_parallel_size": 1, "training": true}, "num_attention_heads": 32, "num_hidden_layers": 16, "num_key_value_heads": 8, "pad_token_id": 128257, "pretraining_tp": 1, "rms_norm_eps": 1e-05, "rope_scaling": {"factor": 32.0, "high_freq_factor": 4.0, "low_freq_factor": 1.0, "original_max_position_embeddings": 8192, "rope_type": "llama3"}, "rope_theta": 500000.0, "tie_word_embeddings": true, "torch_dtype": "bfloat16", "use_cache": true, "vocab_size": 128258}

neuronxcc-2.15.128.0+56dc5a86/0_REGISTRY/0.0.25.dev0/training/llama/meta-llama/Llama-3.2-1B/63c097a93835cfd20b01.json

@@ -0,0 +1 @@
+{"architectures": ["LlamaForCausalLM"], "attention_bias": false, "attention_dropout": 0.0, "bos_token_id": 128256, "eos_token_id": 128257, "head_dim": 64, "hidden_act": "silu", "hidden_size": 2048, "initializer_range": 0.02, "intermediate_size": 8192, "max_position_embeddings": 131072, "mlp_bias": false, "model_type": "llama", "neuron": {"compiler_version": "2.15.128.0+56dc5a86", "input_specs": {"chosen": ["<|im_start|>user\nGiven $f(x) = \\frac{\\sqrt{2x-6}}{x-3}$, what is the smallest possible integer value for $x$ such that $f(x)$ has a real number value?<|im_end|>\n<|im_start|>assistant\nI notice that the function $f(x)$ involves a square root in the numerator, so I need to make sure that the radicand (the expression under the square root) is non-negative.\nThis means that $2x-6 \\geq 0$, or equivalently, $x \\geq 3$.\nHowever, I also notice that the function has a fraction, and I need to avoid dividing by zero.\nThis means that $x-3 \\neq 0$, or equivalently, $x \\neq 3$.\nSo, combining these two conditions, I get that $x > 3$.\nThe question asks for the smallest possible integer value for $x$, so I need to find the first integer that is larger than 3.\nI can easily see that this is 4, so the smallest possible integer value for $x$ is 4.\n# Answer\n\n4<|im_end|>\n"], "chosen_attention_mask": [1, 512], "chosen_input_ids": [1, 512], "chosen_labels": [1, 512], "prompt": ["Given $f(x) = \\frac{\\sqrt{2x-6}}{x-3}$, what is the smallest possible integer value for $x$ such that $f(x)$ has a real number value?"], "prompt_attention_mask": [1, 512], "prompt_input_ids": [1, 512], "question": ["Given $f(x) = \\frac{\\sqrt{2x-6}}{x-3}$, what is the smallest possible integer value for $x$ such that $f(x)$ has a real number value?"], "rejected": ["<|im_start|>user\nGiven $f(x) = \\frac{\\sqrt{2x-6}}{x-3}$, what is the smallest possible integer value for $x$ such that $f(x)$ has a real number value?<|im_end|>\n<|im_start|>assistant\nIn order for $f(x)$ to have a real number value, the expression inside the square root in the numerator must be non-negative and the denominator must not be 0. So we have the two conditions $2x-6\\ge0 \\Rightarrow x \\ge 3$ and $x-3 \\ne 0 \\Rightarrow x \\ne 3$. We see that $x=\\boxed{4}$ is the smallest integer value that satisfies both conditions.<|im_end|>\n"], "rejected_attention_mask": [1, 512], "rejected_input_ids": [1, 512], "rejected_labels": [1, 512], "source": ["prm_dpo_pairs"]}, "model_class": "PeftModelForCausalLM", "num_neuron_cores_per_node": 2, "pipeline_parallel_size": 1, "precision": "bfloat16", "tensor_parallel_size": 1, "training": true}, "num_attention_heads": 32, "num_hidden_layers": 16, "num_key_value_heads": 8, "pad_token_id": 128257, "pretraining_tp": 1, "rms_norm_eps": 1e-05, "rope_scaling": {"factor": 32.0, "high_freq_factor": 4.0, "low_freq_factor": 1.0, "original_max_position_embeddings": 8192, "rope_type": "llama3"}, "rope_theta": 500000.0, "tie_word_embeddings": true, "torch_dtype": "bfloat16", "use_cache": true, "vocab_size": 128258}

neuronxcc-2.15.128.0+56dc5a86/0_REGISTRY/0.0.25.dev0/training/llama/meta-llama/Llama-3.2-1B/73c216128a1757d24af5.json

@@ -0,0 +1 @@
+{"architectures": ["LlamaForCausalLM"], "attention_bias": false, "attention_dropout": 0.0, "bos_token_id": 128256, "eos_token_id": 128257, "head_dim": 64, "hidden_act": "silu", "hidden_size": 2048, "initializer_range": 0.02, "intermediate_size": 8192, "max_position_embeddings": 131072, "mlp_bias": false, "model_type": "llama", "neuron": {"compiler_version": "2.15.128.0+56dc5a86", "input_specs": {"chosen": ["<|im_start|>user\nAnalyze the use of foreshadowing in The Things They Carried by Tim O'Brien.<|im_end|>\n<|im_start|>assistant\n\"The Things They Carried\" by Tim O'Brien is a collection of short stories reflecting on the author's experiences during the Vietnam War. O'Brien masterfully employs the literary technique of foreshadowing to hint at future events, create suspense, and deepen the emotional impact of the narrative. Here are a few key instances of foreshadowing in the book.\n\n1. Ted Lavender's Death:\nEarly in the first story, \"The Things They Carried,\" O'Brien describes the soldiers carrying various items, including their emotional burdens. One of these soldiers is Ted Lavender, who deals with his anxiety by taking tranquilizers. His reliance on these pills foreshadows his untimely death, which occurs later in the same story when he is shot while returning from relieving himself.\n\n2. Kiowa's Death:\nIn \"Speaking of Courage,\" O'Brien recounts the story of Norman Bowker, who is haunted by the memory of Kiowa's death. Though the actual event has not yet been revealed to the reader, the sense of guilt and trauma in Norman's thoughts foreshadows the tragedy of Kiowa's demise. This event is not fully described until the subsequent story \"Notes,\" where O'Brien reveals how Kiowa drowned in a sewage field after artillery fire.\n\n3. Curt Lemon's Death:\nIn the story \"How to Tell a True War Story,\" O'Brien tells the tale of Curt Lemon and his friend Rat Kiley playing catch with a smoke grenade, seemingly fearless despite the potential danger. This recklessness foreshadows Lemon's death, which happens later in the story, where he dies in a freak accident involving a rigged artillery shell.\n\n4. The Dancing Girl:\nIn \"Style,\" O'Brien introduces a young Vietnamese girl who dances among the rubble of her destroyed village, symbolizing both the innocence and resilience of civilian life amid war. The dance foreshadows the emotional weight soldiers bear following their return to civilian life and helps highlight the continued impact that war has on the lives of those who survive.\n\n5. \"Sweetheart of the Song Tra Bong\":\nIn this story, O'Brien tells the tale of Mary Anne Bell, a young American woman who arrives in Vietnam to be with her boyfriend. Her initial innocence and naivete foreshadow her transformation into a ruthless, aggressive soldier, emphasizing the dehumanizing effects of war and the loss of innocence.\n\nOverall, O'Brien's use of foreshadowing in \"The Things They Carried\" not only builds suspense and maintains reader interest but also adds to the emotional depth and authenticity of the narratives. By offering glimpses of tragic outcomes, the author cultivates a sense of foreboding that mirrors the experiences of the soldiers who lived with the constant threat of death, loss, and trauma during the Vietnam War.<|im_end|>\n"], "chosen_attention_mask": [1, 512], "chosen_input_ids": [1, 512], "chosen_labels": [1, 512], "prompt": ["Analyze the use of foreshadowing in The Things They Carried by Tim O'Brien."], "prompt_attention_mask": [1, 512], "prompt_input_ids": [1, 512], "question": ["Analyze the use of foreshadowing in The Things They Carried by Tim O'Brien."], "rejected": ["<|im_start|>user\nAnalyze the use of foreshadowing in The Things They Carried by Tim O'Brien.<|im_end|>\n<|im_start|>assistant\nThe Things They Carried is a novel by Tim O'Brien that tells the story of a platoon of American soldiers fighting in the Vietnam War. The novel is narrated by O'Brien himself, who also served in the war.\n\nOne of the most striking features of The Things They Carried is its use of foreshadowing. O'Brien frequently hints at events that will happen later in the novel, often in a way that is subtle and understated. This technique creates a sense of suspense and tension in the reader, as they are left wondering what will happen next.\n\nFor example, early in the novel, O'Brien describes the story of a soldier named Kiowa who is killed in action. O'Brien recounts a conversation he had with Kiowa about the fear of death. Kiowa tells O'Brien that he is not afraid to die, because he believes that he will go to heaven. O'Brien then reflects on the possibility of Kiowa's death, and how it would affect him. He writes:\n\n\"I wondered what it would be like to return to the world without Kiowa. The thought filled me with sadness and fear. I had never been close to another man, and I didn't know how I would bear the loss.\"\n\nThis passage foreshadows Kiowa's death, and the impact it will have on O'Brien. O'Brien's fear of losing Kiowa is realized later in the novel, when Kiowa is killed in a tragic accident.\n\nO'Brien also uses foreshadowing to create a sense of foreboding and dread in the reader. For example, in the chapter \"The Lives of the Dead,\" O'Brien describes a vision he has of his dead comrades. He sees them walking towards him, and he knows that they are coming to take him with them. This vision creates a sense of unease in the reader, as they are left wondering what will happen to O'Brien.\n\nThe use of foreshadowing in The Things They Carried is an effective way of creating suspense and tension in the reader. It also helps to develop the themes of death, loss, and fear.<|im_end|>\n"], "rejected_attention_mask": [1, 512], "rejected_input_ids": [1, 512], "rejected_labels": [1, 512], "source": ["ultrachat"]}, "model_class": "PeftModelForCausalLM", "num_neuron_cores_per_node": 2, "pipeline_parallel_size": 1, "precision": "bfloat16", "tensor_parallel_size": 1, "training": true}, "num_attention_heads": 32, "num_hidden_layers": 16, "num_key_value_heads": 8, "pad_token_id": 128257, "pretraining_tp": 1, "rms_norm_eps": 1e-05, "rope_scaling": {"factor": 32.0, "high_freq_factor": 4.0, "low_freq_factor": 1.0, "original_max_position_embeddings": 8192, "rope_type": "llama3"}, "rope_theta": 500000.0, "tie_word_embeddings": true, "torch_dtype": "bfloat16", "use_cache": true, "vocab_size": 128258}

neuronxcc-2.15.128.0+56dc5a86/0_REGISTRY/0.0.25.dev0/training/llama/meta-llama/Llama-3.2-1B/89d956bfe807a8a3447a.json

@@ -0,0 +1 @@
+{"architectures": ["LlamaForCausalLM"], "attention_bias": false, "attention_dropout": 0.0, "bos_token_id": 128256, "eos_token_id": 128257, "head_dim": 64, "hidden_act": "silu", "hidden_size": 2048, "initializer_range": 0.02, "intermediate_size": 8192, "max_position_embeddings": 131072, "mlp_bias": false, "model_type": "llama", "neuron": {"compiler_version": "2.15.128.0+56dc5a86", "input_specs": {"chosen": ["<|im_start|>user\nYou are an AI assistant that follows instruction extremely well. Help as much as you can.\n\nQuestion: Segadores de Vida -  Segadores de Vida is a Christian church located in Hollywood Florida. It is one of the fastest growing churches in the US.[citation needed] The Pastors of the church are Ruddy and Maria Gracia. The church's weekly services are broadcast on Enlace MegaTV and Galavision as well as some local channels. The television program Hechos is viewed in Latin America the United States and Europe.[citation needed] Given a choice of categories company, educational institution, artist, athlete, office holder, mean of transportation, building, natural place, village, animal, plant, album, film or written work, the text refers to which one?\nAnswer:<|im_end|>\n<|im_start|>assistant\n Based on the information provided, the text refers to the category of \"religious institution\" or \"church\".<|im_end|>\n"], "chosen_attention_mask": [1, 512], "chosen_input_ids": [1, 512], "chosen_labels": [1, 512], "prompt": ["You are an AI assistant that follows instruction extremely well. Help as much as you can.\n\nQuestion: Segadores de Vida -  Segadores de Vida is a Christian church located in Hollywood Florida. It is one of the fastest growing churches in the US.[citation needed] The Pastors of the church are Ruddy and Maria Gracia. The church's weekly services are broadcast on Enlace MegaTV and Galavision as well as some local channels. The television program Hechos is viewed in Latin America the United States and Europe.[citation needed] Given a choice of categories company, educational institution, artist, athlete, office holder, mean of transportation, building, natural place, village, animal, plant, album, film or written work, the text refers to which one?\nAnswer:"], "prompt_attention_mask": [1, 512], "prompt_input_ids": [1, 512], "question": ["You are an AI assistant that follows instruction extremely well. Help as much as you can.\n\nQuestion: Segadores de Vida -  Segadores de Vida is a Christian church located in Hollywood Florida. It is one of the fastest growing churches in the US.[citation needed] The Pastors of the church are Ruddy and Maria Gracia. The church's weekly services are broadcast on Enlace MegaTV and Galavision as well as some local channels. The television program Hechos is viewed in Latin America the United States and Europe.[citation needed] Given a choice of categories company, educational institution, artist, athlete, office holder, mean of transportation, building, natural place, village, animal, plant, album, film or written work, the text refers to which one?\nAnswer:"], "rejected": ["<|im_start|>user\nYou are an AI assistant that follows instruction extremely well. Help as much as you can.\n\nQuestion: Segadores de Vida -  Segadores de Vida is a Christian church located in Hollywood Florida. It is one of the fastest growing churches in the US.[citation needed] The Pastors of the church are Ruddy and Maria Gracia. The church's weekly services are broadcast on Enlace MegaTV and Galavision as well as some local channels. The television program Hechos is viewed in Latin America the United States and Europe.[citation needed] Given a choice of categories company, educational institution, artist, athlete, office holder, mean of transportation, building, natural place, village, animal, plant, album, film or written work, the text refers to which one?\nAnswer:<|im_end|>\n<|im_start|>assistant\nbuilding<|im_end|>\n"], "rejected_attention_mask": [1, 512], "rejected_input_ids": [1, 512], "rejected_labels": [1, 512], "source": ["orca_dpo_pairs"]}, "model_class": "PeftModelForCausalLM", "num_neuron_cores_per_node": 2, "pipeline_parallel_size": 1, "precision": "bfloat16", "tensor_parallel_size": 1, "training": true}, "num_attention_heads": 32, "num_hidden_layers": 16, "num_key_value_heads": 8, "pad_token_id": 128257, "pretraining_tp": 1, "rms_norm_eps": 1e-05, "rope_scaling": {"factor": 32.0, "high_freq_factor": 4.0, "low_freq_factor": 1.0, "original_max_position_embeddings": 8192, "rope_type": "llama3"}, "rope_theta": 500000.0, "tie_word_embeddings": true, "torch_dtype": "bfloat16", "use_cache": true, "vocab_size": 128258}

neuronxcc-2.15.128.0+56dc5a86/0_REGISTRY/0.0.25.dev0/training/llama/meta-llama/Llama-3.2-1B/b1d751da51aa6f96caa6.json

@@ -0,0 +1 @@
+{"architectures": ["LlamaForCausalLM"], "attention_bias": false, "attention_dropout": 0.0, "bos_token_id": 128256, "eos_token_id": 128257, "head_dim": 64, "hidden_act": "silu", "hidden_size": 2048, "initializer_range": 0.02, "intermediate_size": 8192, "max_position_embeddings": 131072, "mlp_bias": false, "model_type": "llama", "neuron": {"compiler_version": "2.15.128.0+56dc5a86", "input_specs": {"chosen": ["<|im_start|>user\nDo you know what a Chief Audit Executive (CAE) is?<|im_end|>\n<|im_start|>assistant\nYes, I am familiar with the role of a Chief Audit Executive (CAE). The CAE is a high-level executive who oversees the internal audit function of an organization. They are responsible for ensuring that the organization's risk management, governance, and internal control processes are effective and in compliance with relevant regulations and standards. The CAE reports directly to the board of directors or the audit committee and serves as the primary point of contact for external auditors and regulatory authorities.\n\nKey responsibilities of a Chief Audit Executive typically include:\n\n1. Developing and implementing the organizational internal audit plan, which outlines the objectives, scope, and frequency of audit activities.\n2. Supervising and managing a team of internal auditors, including hiring, training, and performance evaluation.\n3. Ensuring that internal audit reports are accurate, objective, and timely, and that recommendations for improving the organization's operations are effectively communicated to management.\n4. Liaising with senior management and the board to communicate key audit findings, risk management issues, and recommendations for improvement.\n5. Ensuring compliance with relevant laws, regulations, and professional standards, and implementing corrective actions when necessary.\n6. Staying up-to-date on industry best practices, emerging risks, and external threats, and adjusting the internal audit strategy accordingly.\n7. Managing relationships with external auditors, regulatory authorities, and other stakeholders to ensure a coordinated approach to audit activities and a transparent flow of information.<|im_end|>\n"], "chosen_attention_mask": [1, 512], "chosen_input_ids": [1, 512], "chosen_labels": [1, 512], "prompt": ["Do you know what a Chief Audit Executive (CAE) is?"], "prompt_attention_mask": [1, 512], "prompt_input_ids": [1, 512], "question": ["Do you know what a Chief Audit Executive (CAE) is?"], "rejected": ["<|im_start|>user\nDo you know what a Chief Audit Executive (CAE) is?<|im_end|>\n<|im_start|>assistant\nNo, I don't have any information related to your query.<|im_end|>\n"], "rejected_attention_mask": [1, 512], "rejected_input_ids": [1, 512], "rejected_labels": [1, 512], "source": ["sharegpt"]}, "model_class": "PeftModelForCausalLM", "num_neuron_cores_per_node": 2, "pipeline_parallel_size": 1, "precision": "bfloat16", "tensor_parallel_size": 1, "training": true}, "num_attention_heads": 32, "num_hidden_layers": 16, "num_key_value_heads": 8, "pad_token_id": 128257, "pretraining_tp": 1, "rms_norm_eps": 1e-05, "rope_scaling": {"factor": 32.0, "high_freq_factor": 4.0, "low_freq_factor": 1.0, "original_max_position_embeddings": 8192, "rope_type": "llama3"}, "rope_theta": 500000.0, "tie_word_embeddings": true, "torch_dtype": "bfloat16", "use_cache": true, "vocab_size": 128258}

neuronxcc-2.15.128.0+56dc5a86/0_REGISTRY/0.0.25.dev0/training/llama/meta-llama/Llama-3.2-1B/bc356b3fa0e4f8b4178e.json

@@ -0,0 +1 @@
+{"architectures": ["LlamaForCausalLM"], "attention_bias": false, "attention_dropout": 0.0, "bos_token_id": 128256, "eos_token_id": 128257, "head_dim": 64, "hidden_act": "silu", "hidden_size": 2048, "initializer_range": 0.02, "intermediate_size": 8192, "max_position_embeddings": 131072, "mlp_bias": false, "model_type": "llama", "neuron": {"compiler_version": "2.15.128.0+56dc5a86", "input_specs": {"chosen": ["<|im_start|>user\nGiven the English sentence \"I am learning to use a GPT language model,\" please create a program that can accurately convert this sentence into Pig Latin, a language game where the initial consonant or consonant cluster of a word is moved to the end of the word, followed by \"ay\". The resulting Pig Latin sentence should be grammatically correct and accurately convey the original meaning of the English sentence. Furthermore, the program should be able to handle any English sentence inputted by a user, not just this specific example sentence.<|im_end|>\n<|im_start|>assistant\nHere's a simple Python program that converts an English sentence into Pig Latin:\n\n```python\ndef pig_latin(word):\n    vowels = ['a', 'e', 'i', 'o', 'u']\n    \n    # Word starts with a vowel\n    if word[0].lower() in vowels:\n        return word + \"yay\"\n    else:\n        # Find the first vowel position\n        first_vowel_position = 0\n        for char in word:\n            if char.lower() in vowels:\n                break\n            first_vowel_position += 1\n\n        # Move the consonant cluster to the end and add \"ay\"\n        return word[first_vowel_position:] + word[:first_vowel_position] + \"ay\"\n\ndef pig_latin_sentence(sentence):\n    words = sentence.split(\" \")\n    result = []\n    for word in words:\n        result.append(pig_latin(word))\n    return \" \".join(result)\n\nif __name__ == \"__main__\":\n    english_sentence = \"I am learning to use a GPT language model\"\n    pig_latin_sentence = pig_latin_sentence(english_sentence)\n    print(pig_latin_sentence)\n```\nThis program defines two functions: `pig_latin()` to convert a single word into Pig Latin and `pig_latin_sentence()` to handle a full sentence. When you run this program, it will output the Pig Latin version of the given English sentence:\n\n```\nIyay amay earninglay otay useyay ay GPTyay anguagelay odelmay\n```\n\nYou can replace the `english_sentence` variable with any English sentence you'd like to convert into Pig Latin. The program will adjust accordingly.<|im_end|>\n"], "chosen_attention_mask": [1, 512], "chosen_input_ids": [1, 512], "chosen_labels": [1, 512], "prompt": ["Given the English sentence \"I am learning to use a GPT language model,\" please create a program that can accurately convert this sentence into Pig Latin, a language game where the initial consonant or consonant cluster of a word is moved to the end of the word, followed by \"ay\". The resulting Pig Latin sentence should be grammatically correct and accurately convey the original meaning of the English sentence. Furthermore, the program should be able to handle any English sentence inputted by a user, not just this specific example sentence."], "prompt_attention_mask": [1, 512], "prompt_input_ids": [1, 512], "question": ["Given the English sentence \"I am learning to use a GPT language model,\" please create a program that can accurately convert this sentence into Pig Latin, a language game where the initial consonant or consonant cluster of a word is moved to the end of the word, followed by \"ay\". The resulting Pig Latin sentence should be grammatically correct and accurately convey the original meaning of the English sentence. Furthermore, the program should be able to handle any English sentence inputted by a user, not just this specific example sentence."], "rejected": ["<|im_start|>user\nGiven the English sentence \"I am learning to use a GPT language model,\" please create a program that can accurately convert this sentence into Pig Latin, a language game where the initial consonant or consonant cluster of a word is moved to the end of the word, followed by \"ay\". The resulting Pig Latin sentence should be grammatically correct and accurately convey the original meaning of the English sentence. Furthermore, the program should be able to handle any English sentence inputted by a user, not just this specific example sentence.<|im_end|>\n<|im_start|>assistant\nSure, I can help you with that! Here's a Python program that can convert an input English sentence into Pig Latin:\n```python\ndef pig_latin(sentence):\n    # Split the sentence into words\n    words = sentence.split()\n    \n    # Create a set to store the vowels\n    vowels = set(\"aeiou\")\n    \n    # Create a list to store the Pig Latin form of each word\n    pig_latin_words = []\n    \n    # Loop through each word in the sentence\n    for word in words:\n        word = word.capitalize() # Capitalize the first letter of the word\n        stripped_word = word.replace(\"a\", \"\").replace(\"e\", \"\").replace(\"i\", \"\").replace(\"o\", \"\").replace(\"u\", \"\") # Remove any vowels from the word\n        \n        # Check if the word ends in a vowel or \"y\"\n        if stripped_word[-1] in vowels or stripped_word[-1] == \"y\":\n            pig_latin_words.append(word + \"ay\")\n        else:\n            # If the word doesn't end in a vowel or \"y\", move the first letter to the end of the word\n            pig_latin_words.append(word[1:] + word[0] + \"ay\")\n    \n    # Join the Pig Latin words back into a sentence\n    pig_latin_sentence = \" \".join(pig_latin_words)\n    \n    return pig_latin_sentence\n```\nTo use this program, you can call the `pig_latin()` function and pass in an English sentence as an argument:\n```python\nenglish_sentence = \"I am learning to use a GPT language model.\"\npig_latin_sentence = pig_latin(english_sentence)\nprint(pig_latin_sentence)\n```\nThis will output the Pig Latin version of the input sentence:\n```\nIway amway unnestay abway otay ogpay otelmay ogroday unmaya otamday olpay otay.\n```<|im_end|>\n"], "rejected_attention_mask": [1, 512], "rejected_input_ids": [1, 512], "rejected_labels": [1, 512], "source": ["evol_instruct"]}, "model_class": "PeftModelForCausalLM", "num_neuron_cores_per_node": 2, "pipeline_parallel_size": 1, "precision": "bfloat16", "tensor_parallel_size": 1, "training": true}, "num_attention_heads": 32, "num_hidden_layers": 16, "num_key_value_heads": 8, "pad_token_id": 128257, "pretraining_tp": 1, "rms_norm_eps": 1e-05, "rope_scaling": {"factor": 32.0, "high_freq_factor": 4.0, "low_freq_factor": 1.0, "original_max_position_embeddings": 8192, "rope_type": "llama3"}, "rope_theta": 500000.0, "tie_word_embeddings": true, "torch_dtype": "bfloat16", "use_cache": true, "vocab_size": 128258}

neuronxcc-2.15.128.0+56dc5a86/0_REGISTRY/0.0.25.dev0/training/llama/meta-llama/Llama-3.2-1B/be3c7bf559b3b8107ceb.json

@@ -0,0 +1 @@
+{"architectures": ["LlamaForCausalLM"], "attention_bias": false, "attention_dropout": 0.0, "bos_token_id": 128256, "eos_token_id": 128257, "head_dim": 64, "hidden_act": "silu", "hidden_size": 2048, "initializer_range": 0.02, "intermediate_size": 8192, "max_position_embeddings": 131072, "mlp_bias": false, "model_type": "llama", "neuron": {"compiler_version": "2.15.128.0+56dc5a86", "input_specs": {"chosen": ["<|im_start|>user\nGive me a database table that I can manually write SQL queries based on the data sample set. \n\nLets make it about LinkedIn Data as an example<|im_end|>\n<|im_start|>assistant\nHere's a sample database schema for LinkedIn data with five tables: Users, Connections, Companies, Jobs, and Skills. You can use these tables to write your SQL queries.\n\n1. Users (UserID, FirstName, LastName, Title, Industry, Location, Email)\n\nExample data:\n```sql\n| UserID | FirstName | LastName |           Title           |   Industry   |   Location  |         Email         |\n|--------|-----------|----------|---------------------------|--------------|-------------|-----------------------|\n| 1      | Alice     | Smith    | Software Engineer         | Technology   | New York    | [email protected] |\n| 2      | Bob       | Johnson  | Product Manager           | Technology   | San Francisco | [email protected] |\n| 3      | Carol     | Williams | Data Scientist            | Technology   | Los Angeles | [email protected] |\n```\n1. Connections (ConnectionID, UserID1, UserID2)\n\nExample data:\n```lua\n| ConnectionID | UserID1 | UserID2 |\n|--------------|---------|---------|\n| 1            | 1       | 2       |\n| 2            | 1       | 3       |\n| 3            | 2       | 3       |\n```\n1. Companies (CompanyID, CompanyName, Industry, Location, Size)\n\nExample data:\n```sql\n| CompanyID | CompanyName |   Industry   |   Location  |   Size  |\n|-----------|-------------|--------------|-------------|---------|\n| 1         | TechCorp    | Technology   | New York    | 5000    |\n| 2         | FinHub      | Finance      | San Francisco | 10000  |\n| 3         | HealthPlus  | Healthcare   | Los Angeles | 2500    |\n```\n1. Jobs (JobID, UserID, CompanyID, Title, StartDate, EndDate)\n\nExample data:\n```yaml\n| JobID | UserID | CompanyID |           Title           |  StartDate  |  EndDate   |\n|-------|--------|-----------|---------------------------|-------------|------------|\n| 1     | 1      | 1         | Software Engineer         | 2020-01-01  | 2021-12-31 |\n| 2     | 2      | 2         | Product Manager           | 2019-05-01  | 2022-02-28 |\n| 3     | 3      | 3         | Data Scientist            | 2018-10-01  | NULL       |\n```\n1. Skills (SkillID, UserID, SkillName, Proficiency)\n\nExample data:\n```lua\n| SkillID | UserID |   SkillName   | Proficiency |\n|---------|--------|---------------|-------------|\n| 1       | 1      | Python        | Advanced    |\n| 2       | 1      | Java          | Intermediate |\n| 3       | 2      | Product Management | Expert    |\n| 4       | 3      | Machine Learning | Advanced   |\n```\nNow, you can create your SQL queries using these tables to analyze and explore the LinkedIn data.<|im_end|>\n<|im_start|>user\nBased on SQL from Table 1, \n\nCan you give me some SQL questions I can ask, and have someone write them manually on a piece of paper by showing this Table. Also, can you give me the answers to those questions. I only 3 questions and answers.<|im_end|>\n<|im_start|>assistant\nSure, here are three sample SQL queries based on the Users table, along with the answers to those queries:\n\n1. How many users are there in the database?\n   ```sql\n   SELECT COUNT(*) FROM Users;\n   ```\n   Answer: 3\n\n2. List all users and their corresponding email addresses.\n   ```sql\n   SELECT FirstName, LastName, Email FROM Users;\n   ```\n   Answer:\n   ```\n   | FirstName | LastName |         Email          |\n   |-----------|----------|-----------------------|\n   | Alice     | Smith    | [email protected]  |\n   | Bob       | Johnson  | [email protected]  |\n   | Carol     | Williams | [email protected] |\n   ```\n\n3. How many users work in the Technology industry?\n   ```sql\n   SELECT COUNT(*) FROM Users WHERE Industry = 'Technology'\n   ```\n   Answer: 3<|im_end|>\n"], "chosen_attention_mask": [1, 512], "chosen_input_ids": [1, 512], "chosen_labels": [1, 512], "prompt": ["Give me a database table that I can manually write SQL queries based on the data sample set. \n\nLets make it about LinkedIn Data as an example"], "prompt_attention_mask": [1, 512], "prompt_input_ids": [1, 512], "question": ["Give me a database table that I can manually write SQL queries based on the data sample set. \n\nLets make it about LinkedIn Data as an example"], "rejected": ["<|im_start|>user\nGive me a database table that I can manually write SQL queries based on the data sample set. \n\nLets make it about LinkedIn Data as an example<|im_end|>\n<|im_start|>assistant\nHere's a sample database schema for LinkedIn data with five tables: Users, Connections, Companies, Jobs, and Skills. You can use these tables to write your SQL queries.\n\n1. Users (UserID, FirstName, LastName, Title, Industry, Location, Email)\n\nExample data:\n```sql\n| UserID | FirstName | LastName |           Title           |   Industry   |   Location  |         Email         |\n|--------|-----------|----------|---------------------------|--------------|-------------|-----------------------|\n| 1      | Alice     | Smith    | Software Engineer         | Technology   | New York    | [email protected] |\n| 2      | Bob       | Johnson  | Product Manager           | Technology   | San Francisco | [email protected] |\n| 3      | Carol     | Williams | Data Scientist            | Technology   | Los Angeles | [email protected] |\n```\n1. Connections (ConnectionID, UserID1, UserID2)\n\nExample data:\n```lua\n| ConnectionID | UserID1 | UserID2 |\n|--------------|---------|---------|\n| 1            | 1       | 2       |\n| 2            | 1       | 3       |\n| 3            | 2       | 3       |\n```\n1. Companies (CompanyID, CompanyName, Industry, Location, Size)\n\nExample data:\n```sql\n| CompanyID | CompanyName |   Industry   |   Location  |   Size  |\n|-----------|-------------|--------------|-------------|---------|\n| 1         | TechCorp    | Technology   | New York    | 5000    |\n| 2         | FinHub      | Finance      | San Francisco | 10000  |\n| 3         | HealthPlus  | Healthcare   | Los Angeles | 2500    |\n```\n1. Jobs (JobID, UserID, CompanyID, Title, StartDate, EndDate)\n\nExample data:\n```yaml\n| JobID | UserID | CompanyID |           Title           |  StartDate  |  EndDate   |\n|-------|--------|-----------|---------------------------|-------------|------------|\n| 1     | 1      | 1         | Software Engineer         | 2020-01-01  | 2021-12-31 |\n| 2     | 2      | 2         | Product Manager           | 2019-05-01  | 2022-02-28 |\n| 3     | 3      | 3         | Data Scientist            | 2018-10-01  | NULL       |\n```\n1. Skills (SkillID, UserID, SkillName, Proficiency)\n\nExample data:\n```lua\n| SkillID | UserID |   SkillName   | Proficiency |\n|---------|--------|---------------|-------------|\n| 1       | 1      | Python        | Advanced    |\n| 2       | 1      | Java          | Intermediate |\n| 3       | 2      | Product Management | Expert    |\n| 4       | 3      | Machine Learning | Advanced   |\n```\nNow, you can create your SQL queries using these tables to analyze and explore the LinkedIn data.<|im_end|>\n<|im_start|>user\nBased on SQL from Table 1, \n\nCan you give me some SQL questions I can ask, and have someone write them manually on a piece of paper by showing this Table. Also, can you give me the answers to those questions. I only 3 questions and answers.<|im_end|>\n<|im_start|>assistant\n Here are three SQL questions based on the Users table, along with the example queries and their resulting data when applied to the sample data provided. Please note that the queries and answers assume manual entry and do not have actually run the SQL or connect to any database.\n\n 1. Which user worked in the Technology industry in New York and has the first name 'Alice'?\n   SQL Query:\n   ```sql\n   SELECT * FROM Users WHERE FirstName = 'Alice' AND Industry = 'Technology' AND Location = 'New York';\n   ```\n   Resulting Data (if any):\n   ```\n   | UserID | FirstName | LastName |           Title           |   Industry   |   Location  |         Email         |\n   |--------|-----------|----------|---------------------------|--------------|-------------|-----------------------|\n   | 1      | Alice     | Smith    | Software Engineer         | Technology   | New York    | [email protected] |\n   ```\n\n   Answers: There is one user that matches the criteria. Alice Smith is from New York and belongs to the Technology industry.\n\n 2. What are the titles of all users connected to Bob Johnson (UserID = 2)?\n   SQL Query:\n   ```sql\n   SELECT Users.Title FROM Users JOIN Connections ON Users.UserID = Connections.UserID2 WHERE Connections.UserID1 = 2;\n   ```\n   Resulting Data (if any):\n   ```\n   | Title     |\n   |-----------|\n   | Product Manager |\n   | Software Engineer |\n   | Data Scientist |\n   ```\n\n   Answers: The users connected to Bob Johnson include a Software Engineer (Alice Smith), a Product Manager (Bob Johnson himself), and a Data Scientist (Carol Williams). So, the query returns their titles: Product Manager, Software Engineer, and Data Scientist.\n\n 3. What is the most common industry among LinkedIn users in Los Angeles?\n   To find the answer to this question, we first need to prepare a schema that counts the number of users in each industry in Los Angeles. Here's an intermediate query to create and select data from a virtual table that stores the results:\n   ```sql\n   WITH IndustryCounts AS (\n       SELECT\n           Industries.Industry,\n           COUNT(Users.UserID) AS UsersCount\n       FROM\n           Users\n       JOIN\n           Companies ON Users.Location = Companies.Location\n           AND Users.Industry = Companies.Industry -- This join is only for filtering Users and industries for Los Angeles\n       JOIN\n           (SELECT Industry FROM Users UNION ALL SELECT Industry FROM Companies) AS Industries\n           ON Industries.Industry = Companies.Industry\n           OR Industries.Industry = Users.Industry\n       WHERE\n           Users.Location = 'Los Angeles'\n       GROUP BY\n           Industries.Industry\n   )\n\n   -- Query to find the most common industry\n   SELECT\n       Industry,\n       UsersCount\n   FROM\n       IndustryCounts\n   ORDER BY\n       UsersCount DESC\n   LIMIT\n       1;\n   ```\n   Resulting Data (if any, based on our sample data):\n   ```\n   | Industry   | UsersCount |\n   |------------|------------|\n   | Healthcare | 1          |\n   | Technology | 1          |\n   | Finance    | 2          |\n   ```\n\n   Answers: There are only three industries presented in the sample data for Los Angeles. Based on our example data, the most common industry among LinkedIn users in Los Angeles is Finance, with two counts (presumably, Bob Johnson and hypothetical data). Note that this answer might change once you add more real or diverse data to the dataset.<|im_end|>\n"], "rejected_attention_mask": [1, 512], "rejected_input_ids": [1, 512], "rejected_labels": [1, 512], "source": ["Dove"]}, "model_class": "PeftModelForCausalLM", "num_neuron_cores_per_node": 2, "pipeline_parallel_size": 1, "precision": "bfloat16", "tensor_parallel_size": 1, "training": true}, "num_attention_heads": 32, "num_hidden_layers": 16, "num_key_value_heads": 8, "pad_token_id": 128257, "pretraining_tp": 1, "rms_norm_eps": 1e-05, "rope_scaling": {"factor": 32.0, "high_freq_factor": 4.0, "low_freq_factor": 1.0, "original_max_position_embeddings": 8192, "rope_type": "llama3"}, "rope_theta": 500000.0, "tie_word_embeddings": true, "torch_dtype": "bfloat16", "use_cache": true, "vocab_size": 128258}