DeepSeek-R1-NextN
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View details ↗DISCOVER & COMPARE
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View details ↗DeepSeek-V3-NextN
lmsysNextN layer exported for deepseek-ai/DeepSeek-V3 model with script. Used for speculative decoding in SGLang.
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View details ↗OpenAI gpt-oss 120B EAGLE 3 checkpoint, supported by the SpecForge Team, particularly Yikai Zhu, Shenggui Li, and the team members.
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View details ↗fastchat-t5-3b-v1.0
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View details ↗gpt-oss-120b-bf16
lmsysThis model is the bf16 version converted from openai/gpt-oss-120b. You can use this model in SGLang with the following instructions.
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View details ↗gpt-oss-20b-bf16
lmsysThis model is the bf16 version converted from openai/gpt-oss-20b. You can use this model in SGLang with the following instructions.
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View details ↗longchat-13b-16k
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View details ↗longchat-7b-16k
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View details ↗longchat-7b-v1.5-32k
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View details ↗**SpecBundle** is an open-source initiative, jointly driven by the community and industry, to democratize speculative decoding by providing high-performance speculative decoding draft weights for mainstream open-source models. This checkpoint was trained by the **Nex-AGI** Team and released as the **phase 1 of SpecBundle release**. We regenerated the responses in the mlabonne/open-perfectblend and trained the model on 1.4M data samples for 2 epochs. This checkpoint was trained using the **SpecForge** framework. We sincerely appreciate the collective efforts from both the developers in the open-source community and our industrial partners, especially Ant Group AQ Team, Meituan, Nex-AGI (Qiji Zhifeng), EigenAI for their invaluable contributions to the release of SpecBundle Phase 1.
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View details ↗vicuna-13b-delta-v0
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View details ↗vicuna-13b-v1.1
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View details ↗vicuna-13b-v1.3
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View details ↗vicuna-13b-v1.5
lmsysVicuna is a chat assistant trained by fine-tuning Llama 2 on user-shared conversations collected from ShareGPT. The primary use of Vicuna is research on large language models and chatbots. The primary intended users of the model are researchers and hobbyists in natural language processing, machine learning, and artificial intelligence. Vicuna v1.5 is fine-tuned from Llama 2 with supervised instruction fine-tuning. The training data is around 125K conversations collected from ShareGPT.com. See more details in the "Training Details of Vicuna Models" section in the appendix of this paper.
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View details ↗vicuna-13b-v1.5-16k
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View details ↗vicuna-33b-v1.3
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View details ↗vicuna-7b-v1.3
lmsysVicuna is a chat assistant trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT. The primary use of Vicuna is research on large language models and chatbots. The primary intended users of the model are researchers and hobbyists in natural language processing, machine learning, and artificial intelligence. Vicuna v1.3 is fine-tuned from LLaMA with supervised instruction fine-tuning. The training data is around 125K conversations collected from ShareGPT.com. See more details in the "Training Details of Vicuna Models" section in the appendix of this paper.
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View details ↗vicuna-7b-v1.5
lmsysVicuna is a chat assistant trained by fine-tuning Llama 2 on user-shared conversations collected from ShareGPT. - **Developed by:** LMSYS - **Model type:** An auto-regressive language model based on the transformer architecture - **License:** Llama 2 Community License Agreement - **Finetuned from model:** Llama 2 - **Repository:** https://github.com/lm-sys/FastChat - **Blog:** https://lmsys.org/blog/2023-03-30-vicuna/ - **Paper:** https://arxiv.org/abs/2306.05685 - **Demo:** https://chat.lmsys.org/
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View details ↗vicuna-7b-v1.5-16k
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