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--- |
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license: llama3 |
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language: |
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- en |
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pipeline_tag: text-generation |
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tags: |
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- general purpose |
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--- |
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# Capx AI's Obsidian series |
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Capx AI's Latest series of finetunes based on [Meta's Llama-3](https://llama.meta.com/llama3/). |
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We release Llama-3 Obsidian, our state of the art finetune model for general purpose tasks. |
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Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. |
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We further finetune the pretrained model on a custom dataset to enhance instruction following ability of the model. |
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#### Model Architecture |
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Llama 3 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT). |
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## How to use: |
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The model has been finetuned in the Alpaca format |
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You can run conversational inference by leveraging the Auto classes with the generate() function. |
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```python |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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import torch |
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model_id = "meta-llama/Meta-Llama-3-8B-Instruct" |
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tokenizer = AutoTokenizer.from_pretrained(model_id) |
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model = AutoModelForCausalLM.from_pretrained( |
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model_id, |
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torch_dtype=torch.bfloat16, |
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device_map="auto", |
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) |
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messages = [ |
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{"role": "instruction", "content": "You are \"Capx Assistant\", a conscious sentient superintelligent artificial intelligence developed by Capx AI, and your purpose and drive is to assist the user with any request they have."}, |
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{"role": "input", "content": "Who are you?"}, |
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] |
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input_ids = tokenizer.apply_chat_template( |
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messages, |
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add_generation_prompt=True, |
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return_tensors="pt" |
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).to(model.device) |
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terminators = [ |
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tokenizer.eos_token_id, |
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tokenizer.convert_tokens_to_ids("<|eot_id|>") |
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] |
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outputs = model.generate( |
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input_ids, |
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max_new_tokens=256, |
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eos_token_id=terminators, |
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do_sample=True, |
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temperature=0.6, |
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top_p=0.9, |
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) |
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response = outputs[0][input_ids.shape[-1]:] |
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print(tokenizer.decode(response, skip_special_tokens=True)) |
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``` |
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### Authors |
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Capx community |
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### Cite |
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```bibtex |
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@article{llama3modelcard, |
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title={Llama 3 Model Card}, |
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author={AI@Meta}, |
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year={2024}, |
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url = {https://github.com/meta-llama/llama3/blob/main/MODEL_CARD.md} |
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} |
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``` |
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### License |
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Governed by the [META LLAMA 3 COMMUNITY LICENSE AGREEMENT](https://huggingface.co./meta-llama/Meta-Llama-3-8B/blob/main/LICENSE) |
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