add qwen1.5 moe
Former-commit-id: 3ea94f0d12cec25ac694a2c4ae8971c356990b61
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@@ -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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@@ -138,12 +138,11 @@ Compared to ChatGLM's [P-Tuning](https://github.com/THUDM/ChatGLM2-6B/tree/main/
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| [InternLM2](https://huggingface.co/internlm) | 7B/20B | wqkv | intern2 |
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| [LLaMA](https://github.com/facebookresearch/llama) | 7B/13B/33B/65B | q_proj,v_proj | - |
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| [LLaMA-2](https://huggingface.co/meta-llama) | 7B/13B/70B | q_proj,v_proj | llama2 |
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| [Mistral](https://huggingface.co/mistralai) | 7B | q_proj,v_proj | mistral |
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| [Mixtral](https://huggingface.co/mistralai) | 8x7B | q_proj,v_proj | mistral |
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| [Mistral/Mixtral](https://huggingface.co/mistralai) | 7B/8x7B | q_proj,v_proj | mistral |
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| [OLMo](https://huggingface.co/allenai) | 1B/7B | att_proj | olmo |
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| [Phi-1.5/2](https://huggingface.co/microsoft) | 1.3B/2.7B | q_proj,v_proj | - |
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| [Qwen](https://huggingface.co/Qwen) | 1.8B/7B/14B/72B | c_attn | qwen |
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| [Qwen1.5](https://huggingface.co/Qwen) | 0.5B/1.8B/4B/7B/14B/72B | q_proj,v_proj | qwen |
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| [Qwen1.5 (MoE)](https://huggingface.co/Qwen) | 0.5B/1.8B/4B/7B/14B/72B | q_proj,v_proj | qwen |
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| [StarCoder2](https://huggingface.co/bigcode) | 3B/7B/15B | q_proj,v_proj | - |
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| [XVERSE](https://huggingface.co/xverse) | 7B/13B/65B | q_proj,v_proj | xverse |
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| [Yi](https://huggingface.co/01-ai) | 6B/9B/34B | q_proj,v_proj | yi |
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@@ -716,6 +715,7 @@ docker compose -f ./docker-compose.yml up -d
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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. Weller et al. FollowIR: Evaluating and Teaching Information Retrieval Models to Follow Instructions. 2024. [[arxiv]](https://arxiv.org/abs/2403.15246)
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1. Hongbin Na. CBT-LLM: A Chinese Large Language Model for Cognitive Behavioral Therapy-based Mental Health Question Answering. 2024. [[arxiv]](https://arxiv.org/abs/2403.16008)
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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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