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--- |
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license: apache-2.0 |
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tags: |
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- moe |
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- frankenmoe |
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- merge |
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- mergekit |
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- lazymergekit |
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- indischepartij/MiniCPM-3B-Hercules-v2.0 |
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- indischepartij/MiniCPM-3B-OpenHermes-2.5-v2 |
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- indischepartij/MiniCPM-3B-Bacchus |
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base_model: |
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- indischepartij/MiniCPM-3B-Hercules-v2.0 |
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- indischepartij/MiniCPM-3B-OpenHermes-2.5-v2 |
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- indischepartij/MiniCPM-3B-Bacchus |
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model-index: |
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- name: MaxiCPM-3x3B-Test |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: AI2 Reasoning Challenge (25-Shot) |
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type: ai2_arc |
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config: ARC-Challenge |
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split: test |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: acc_norm |
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value: 45.99 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=gmonsoon/MaxiCPM-3x3B-Test |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: HellaSwag (10-Shot) |
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type: hellaswag |
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split: validation |
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args: |
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num_few_shot: 10 |
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metrics: |
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- type: acc_norm |
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value: 71.74 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=gmonsoon/MaxiCPM-3x3B-Test |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MMLU (5-Shot) |
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type: cais/mmlu |
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config: all |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 52.88 |
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name: accuracy |
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source: |
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url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=gmonsoon/MaxiCPM-3x3B-Test |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: TruthfulQA (0-shot) |
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type: truthful_qa |
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config: multiple_choice |
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split: validation |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: mc2 |
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value: 41.06 |
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source: |
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url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=gmonsoon/MaxiCPM-3x3B-Test |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: Winogrande (5-shot) |
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type: winogrande |
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config: winogrande_xl |
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split: validation |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 66.85 |
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name: accuracy |
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source: |
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url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=gmonsoon/MaxiCPM-3x3B-Test |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: GSM8k (5-shot) |
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type: gsm8k |
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config: main |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 44.88 |
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name: accuracy |
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source: |
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url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=gmonsoon/MaxiCPM-3x3B-Test |
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name: Open LLM Leaderboard |
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--- |
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# MaxiCPM-3x3B-Test |
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MaxiCPM-3x3B-Test is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): |
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* [indischepartij/MiniCPM-3B-Hercules-v2.0](https://huggingface.co./indischepartij/MiniCPM-3B-Hercules-v2.0) |
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* [indischepartij/MiniCPM-3B-OpenHermes-2.5-v2](https://huggingface.co./indischepartij/MiniCPM-3B-OpenHermes-2.5-v2) |
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* [indischepartij/MiniCPM-3B-Bacchus](https://huggingface.co./indischepartij/MiniCPM-3B-Bacchus) |
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## 🧩 Configuration |
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```yaml |
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base_model: openbmb/MiniCPM-2B-dpo-bf16-llama-format |
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experts: |
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- source_model: indischepartij/MiniCPM-3B-Hercules-v2.0 |
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positive_prompts: |
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- "chat" |
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- "assistant" |
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- "tell me" |
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- "explain" |
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- source_model: indischepartij/MiniCPM-3B-OpenHermes-2.5-v2 |
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positive_prompts: |
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- "code" |
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- "python" |
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- "javascript" |
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- "programming" |
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- "algorithm" |
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- source_model: indischepartij/MiniCPM-3B-Bacchus |
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positive_prompts: |
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- "storywriting" |
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- "write" |
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- "scene" |
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- "story" |
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- "character" |
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- "reason" |
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- "math" |
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- "mathematics" |
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- "solve" |
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- "count" |
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dtype: bfloat16 |
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``` |
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## 💻 Usage |
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```python |
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!pip install -qU transformers bitsandbytes accelerate |
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from transformers import AutoTokenizer |
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import transformers |
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import torch |
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model = "gmonsoon/MaxiCPM-3x3B-Test" |
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tokenizer = AutoTokenizer.from_pretrained(model) |
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pipeline = transformers.pipeline( |
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"text-generation", |
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model=model, |
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model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True}, |
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) |
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messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}] |
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prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) |
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95) |
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print(outputs[0]["generated_text"]) |
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``` |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/details_gmonsoon__MaxiCPM-3x3B-Test) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |53.90| |
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|AI2 Reasoning Challenge (25-Shot)|45.99| |
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|HellaSwag (10-Shot) |71.74| |
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|MMLU (5-Shot) |52.88| |
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|TruthfulQA (0-shot) |41.06| |
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|Winogrande (5-shot) |66.85| |
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|GSM8k (5-shot) |44.88| |
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