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README.md
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README.md
@@ -5,7 +5,7 @@
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[](https://github.com/hiyouga/LLaMA-Factory/commits/main)
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[](https://pypi.org/project/llmtuner/)
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[](https://pypi.org/project/llmtuner/)
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[](#projects-using-llama-factory)
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[](#projects-using-llama-factory)
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[](https://github.com/hiyouga/LLaMA-Factory/pulls)
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[](https://discord.gg/rKfvV9r9FK)
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[](https://twitter.com/llamafactory_ai)
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| ------------ | ------- | --------- |
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| python | 3.8 | 3.10 |
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| torch | 1.13.1 | 2.2.0 |
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| transformers | 4.37.2 | 4.38.2 |
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| transformers | 4.37.2 | 4.39.1 |
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| datasets | 2.14.3 | 2.17.1 |
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| accelerate | 0.27.2 | 0.27.2 |
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| peft | 0.9.0 | 0.9.0 |
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| trl | 0.7.11 | 0.7.11 |
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| accelerate | 0.27.2 | 0.28.0 |
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| peft | 0.9.0 | 0.10.0 |
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| trl | 0.8.1 | 0.8.1 |
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| Optional | Minimum | Recommend |
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| ------------ | ------- | --------- |
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| CUDA | 11.6 | 12.2 |
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| deepspeed | 0.10.0 | 0.13.1 |
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| bitsandbytes | 0.39.0 | 0.41.3 |
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| flash-attn | 2.3.0 | 2.5.5 |
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| deepspeed | 0.10.0 | 0.14.0 |
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| bitsandbytes | 0.39.0 | 0.43.0 |
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| flash-attn | 2.3.0 | 2.5.6 |
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### Hardware Requirement
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@@ -690,6 +690,7 @@ docker compose -f ./docker-compose.yml up -d
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1. Wang et al. ESRL: Efficient Sampling-based Reinforcement Learning for Sequence Generation. 2023. [[arxiv]](https://arxiv.org/abs/2308.02223)
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1. Yu et al. Open, Closed, or Small Language Models for Text Classification? 2023. [[arxiv]](https://arxiv.org/abs/2308.10092)
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1. Wang et al. UbiPhysio: Support Daily Functioning, Fitness, and Rehabilitation with Action Understanding and Feedback in Natural Language. 2023. [[arxiv]](https://arxiv.org/abs/2308.10526)
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1. Luceri et al. Leveraging Large Language Models to Detect Influence Campaigns in Social Media. 2023. [[arxiv]](https://arxiv.org/abs/2311.07816)
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1. Zhang et al. Alleviating Hallucinations of Large Language Models through Induced Hallucinations. 2023. [[arxiv]](https://arxiv.org/abs/2312.15710)
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1. Wang et al. Know Your Needs Better: Towards Structured Understanding of Marketer Demands with Analogical Reasoning Augmented LLMs. 2024. [[arxiv]](https://arxiv.org/abs/2401.04319)
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@@ -705,6 +706,9 @@ docker compose -f ./docker-compose.yml up -d
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1. Zhang et al. Enhancing Multilingual Capabilities of Large Language Models through Self-Distillation from Resource-Rich Languages. 2024. [[arxiv]](https://arxiv.org/abs/2402.12204)
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1. Kim et al. Efficient and Effective Vocabulary Expansion Towards Multilingual Large Language Models. 2024. [[arxiv]](https://arxiv.org/abs/2402.14714)
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1. Yu et al. KIEval: A Knowledge-grounded Interactive Evaluation Framework for Large Language Models. 2024. [[arxiv]](https://arxiv.org/abs/2402.15043)
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1. Huang et al. Key-Point-Driven Data Synthesis with its Enhancement on Mathematical Reasoning. 2024. [[arxiv]](https://arxiv.org/abs/2403.02333)
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1. Duan et al. Negating Negatives: Alignment without Human Positive Samples via Distributional Dispreference Optimization. 2024. [[arxiv]](https://arxiv.org/abs/2403.03419)
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1. Xie and Schwertfeger. Empowering Robotics with Large Language Models: osmAG Map Comprehension with LLMs. 2024. [[arxiv]](https://arxiv.org/abs/2403.08228)
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1. **[StarWhisper](https://github.com/Yu-Yang-Li/StarWhisper)**: A large language model for Astronomy, based on ChatGLM2-6B and Qwen-14B.
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1. **[DISC-LawLLM](https://github.com/FudanDISC/DISC-LawLLM)**: A large language model specialized in Chinese legal domain, based on Baichuan-13B, is capable of retrieving and reasoning on legal knowledge.
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1. **[Sunsimiao](https://github.com/thomas-yanxin/Sunsimiao)**: A large language model specialized in Chinese medical domain, based on Baichuan-7B and ChatGLM-6B.
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