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--- |
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license: apache-2.0 |
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datasets: |
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- openbmb/UltraInteract_sft |
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- stingning/ultrachat |
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- openchat/openchat_sharegpt4_dataset |
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- Open-Orca/OpenOrca |
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tags: |
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- reasoning |
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pipeline_tag: text-generation |
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--- |
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# Eurus-7b-sft-GGUF |
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- This is quantized version of [openbmb/Eurus-7b-sft](https://huggingface.co/openbmb/Eurus-7b-sft) created using llama.cpp |
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# Model Description |
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Eurus-7B-SFT is fine-tuned from Mistral-7B on all correct actions in UltraInteract, mixing a small proportion of UltraChat, ShareGPT, and OpenOrca examples. |
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It achieves better performance than other open-source models of similar sizes and even outperforms specialized models in corresponding domains in many cases. |
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## Usage |
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We apply tailored prompts for coding and math, consistent with UltraInteract data formats: |
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**Coding** |
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``` |
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[INST] Write Python code to solve the task: |
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{Instruction} [/INST] |
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``` |
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**Math-CoT** |
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``` |
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[INST] Solve the following math problem step-by-step. |
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Simplify your answer as much as possible. Present your final answer as \\boxed{Your Answer}. |
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{Instruction} [/INST] |
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``` |
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**Math-PoT** |
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``` |
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[INST] Tool available: |
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[1] Python interpreter |
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When you send a message containing Python code to python, it will be executed in a stateful Jupyter notebook environment. |
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Solve the following math problem step-by-step. |
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Simplify your answer as much as possible. |
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{Instruction} [/INST] |
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``` |
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## Evaluation |
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- Eurus, both the 7B and 70B variants, achieve the best overall performance among open-source models of similar sizes. Eurus even outperforms specialized models in corresponding domains in many cases. Notably, Eurus-7B outperforms baselines that are 5× larger, and Eurus-70B achieves better performance than GPT-3.5 Turbo. |
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- Preference learning with UltraInteract can further improve performance, especially in math and the multi-turn ability. |
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<img src="figures_main_exp.png" alt="stats" style="zoom: 40%;" /> |
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