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--- |
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language: |
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- en |
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- zh |
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license: apache-2.0 |
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library_name: transformers |
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datasets: |
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- EleutherAI/pile |
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- togethercomputer/RedPajama-Data-1T |
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- p208p2002/wudao |
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widget: |
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- text: <s> 4 + 3 = |
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model-index: |
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- name: MiniMA-2-3B |
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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: 44.71 |
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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=GeneZC/MiniMA-2-3B |
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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: 69.33 |
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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=GeneZC/MiniMA-2-3B |
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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: 41.22 |
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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=GeneZC/MiniMA-2-3B |
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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: 38.44 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=GeneZC/MiniMA-2-3B |
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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: 66.69 |
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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=GeneZC/MiniMA-2-3B |
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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: 8.11 |
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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=GeneZC/MiniMA-2-3B |
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name: Open LLM Leaderboard |
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--- |
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## MiniMA-2-3B |
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📑 [arXiv](https://arxiv.org/abs/2311.07052) | 👻 [GitHub](https://github.com/GeneZC/MiniMA) | 🤗 [HuggingFace-MiniMA](https://huggingface.co/GeneZC/MiniMA-3B) | 🤗 [HuggingFace-MiniChat](https://huggingface.co/GeneZC/MiniChat-3B) | 🤖 [ModelScope-MiniMA](https://modelscope.cn/models/GeneZC/MiniMA-3B) | 🤖 [ModelScope-MiniChat](https://modelscope.cn/models/GeneZC/MiniChat-3B) | 🤗 [HuggingFace-MiniChat-1.5](https://huggingface.co/GeneZC/MiniChat-1.5-3B) | 🤗 [HuggingFace-MiniMA-2](https://huggingface.co/GeneZC/MiniMA-2-3B) | 🤗 [HuggingFace-MiniChat-2](https://huggingface.co/GeneZC/MiniChat-2-3B) |
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🆕 **Updates from MiniMA-3B**: |
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- continued from MiniMA-3B without distillation; |
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- better data mixture; |
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- more trained tokens. |
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❗ Must comply with LICENSE of LLaMA-2 since it is derived from LLaMA-2. |
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A language model continued from MiniMA-3B. |
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Completing the compute-performance pareto frontier together with MiniMA-3B and other arts. |
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<img src="./teaser_a.jpg" alt="teaser_a" width="700" /> |
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**Standard Benchmarks** |
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|Method|TFLOPs|MMLU (5-shot)|CEval (5-shot)|DROP (3-shot)|HumanEval (0-shot)|BBH (3-shot)|GSM8K (8-shot)| |
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|--|--|--|--|--|--|--|--| |
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|Mamba-2.8B|4.6E9|25.58|24.74|15.72|7.32|29.37|3.49| |
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|ShearedLLaMA-2.7B|0.8E9|26.97|22.88|19.98|4.88|30.48|3.56| |
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|BTLM-3B|11.3E9|27.20|26.00|17.84|10.98|30.87|4.55| |
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|StableLM-3B|72.0E9|44.75|31.05|22.35|15.85|32.59|10.99| |
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|Qwen-1.8B|23.8E9|44.05|54.75|12.97|14.02|30.80|22.97| |
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|Phi-2-2.8B|159.9E9|56.74|34.03|30.74|46.95|44.13|55.42| |
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|LLaMA-2-7B|84.0E9|46.00|34.40|31.57|12.80|32.02|14.10| |
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|| |
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|MiniMA-3B|4.0E9|28.51|28.23|22.50|10.98|31.61|8.11| |
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|MiniChat-3B|4.0E9|38.40|36.48|22.58|18.29|31.36|29.72| |
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|MiniMA-2-3B|13.4E9|40.14|44.65|23.10|14.63|31.43|8.87| |
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|MiniChat-2-3B|13.4E9|46.17|43.91|30.26|22.56|34.95|38.13| |
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The following is an example code snippet to use MiniMA-2-3B: |
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```python |
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import torch |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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# MiniMA |
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tokenizer = AutoTokenizer.from_pretrained("GeneZC/MiniMA-2-3B", use_fast=False) |
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# GPU. |
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model = AutoModelForCausalLM.from_pretrained("GeneZC/MiniMA-2-3B", use_cache=True, device_map="auto", torch_dtype=torch.float16).eval() |
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# CPU. |
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# model = AutoModelForCausalLM.from_pretrained("GeneZC/MiniMA-2-3B", use_cache=True, device_map="cpu", torch_dtype=torch.float16).eval() |
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prompt = "Question: Sherrie tells the truth. Vernell says Sherrie tells the truth. Alexis says Vernell lies. Michaela says Alexis tells the truth. Elanor says Michaela tells the truth. Does Elanor tell the truth?\nAnswer: No\n\nQuestion: Kristian lies. Sherrie says Kristian lies. Delbert says Sherrie lies. Jerry says Delbert tells the truth. Shalonda says Jerry tells the truth. Does Shalonda tell the truth?\nAnswer: No\n\nQuestion: Vina tells the truth. Helene says Vina lies. Kandi says Helene tells the truth. Jamey says Kandi lies. Ka says Jamey lies. Does Ka tell the truth?\nAnswer: No\n\nQuestion: Christie tells the truth. Ka says Christie tells the truth. Delbert says Ka lies. Leda says Delbert tells the truth. Lorine says Leda tells the truth. Does Lorine tell the truth?\nAnswer:" |
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input_ids = tokenizer([prompt]).input_ids |
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output_ids = model.generate( |
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torch.as_tensor(input_ids).cuda(), |
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do_sample=True, |
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temperature=0.7, |
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max_new_tokens=1024, |
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) |
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output_ids = output_ids[0][len(input_ids[0]):] |
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output = tokenizer.decode(output_ids, skip_special_tokens=True).strip() |
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# output: "No" |
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``` |
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## Bibtex |
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|
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```bibtex |
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@article{zhang2023law, |
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title={Towards the Law of Capacity Gap in Distilling Language Models}, |
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author={Zhang, Chen and Song, Dawei and Ye, Zheyu and Gao, Yan}, |
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year={2023}, |
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url={https://arxiv.org/abs/2311.07052} |
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} |
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``` |
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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_GeneZC__MiniMA-2-3B) |
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|
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |44.75| |
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|AI2 Reasoning Challenge (25-Shot)|44.71| |
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|HellaSwag (10-Shot) |69.33| |
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|MMLU (5-Shot) |41.22| |
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|TruthfulQA (0-shot) |38.44| |
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|Winogrande (5-shot) |66.69| |
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|GSM8k (5-shot) | 8.11| |
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