Infinity-Instruct-3M-0625-Yi-1.5-9B is an opensource supervised instruction tuning model without reinforcement learning from human feedback (RLHF). This model is just finetuned on Infinity-Instruct-3M and Infinity-Instruct-0625 and showing favorable results on AlpacaEval 2.0 and MT-Bench. Infinity-Instruct-3M-0625-Yi-1.5-9B is tuned on Million-level instruction dataset Infinity-Instruct. First, we apply the foundational dataset Infinity-Instruct-3M to improve the foundational ability (math & code) of Yi-1.5-9B, and get the foundational instruct model Infinity-Instruct-3M-Yi-1.5-9B. Then we finetune the Infinity-Instruct-3M-Yi-1.5-9B to get the stronger chat model Infinity-Instruct-3M-0625-Yi-1.5-9B. Here is the training hyperparamers. Thanks to FlagScale, we could concatenate multiple training samples to remove padding token and apply diverse acceleration techniques to the traning procudure. It effectively reduces our training costs. We will release our code in the near future!
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Beijing Academy of Artificial Intelligence (BAAI) [Paper][Code][🤗] (would be released soon) Infinity-Instruct-7M-Gen-Llama3.1-8B is an opensource supervised instruction tuning model without reinforcement learning from human feedback (RLHF). This model is just finetuned on Infinity-Instruct-7M and Infinity-Instruct-Gen and showing favorable results on AlpacaEval 2.0 compared to GPT4. - 🔥🔥🔥[2024/08/02] We release the model weights of InfInstruct-Llama3.1-70B Gen, InfInstruct-Llama3.1-8B Gen, InfInstruct-Mistral-7B Gen.
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JudgeLM-13B-v1.0
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JudgeLM-33B-v1.0
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JudgeLM-7B-v1.0
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LLARA-beir
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LLARA-document
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LLARA-passage
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LLARA-pretrain
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llm-embedder
BAAIModel List | FAQ | Usage | Evaluation | Train | Contact | Citation | License More details please refer to our Github: FlagEmbedding. **Hiring:** We're seeking experienced NLP researchers and intern students focusing on dense retrieval and retrieval-augmented LLMs. If you're interested, please feel free to reach out to us via email at zhengliu1026@gmail.com.
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MS-Human-700
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MTVCraft
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OmniGen-v1
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