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README.md
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<em>[Paper][Code][π€] (would be released soon)</em>
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</p>
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Infinity-Instruct-7M-
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## **News**
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- π₯π₯π₯[2024/08/02] We release the model weights of [InfInstruct-Llama3.1-70B
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- π₯π₯π₯[2024/08/02] We release the 7M foundational dataset [Infinity-Instruct-7M](https://huggingface.co/datasets/BAAI/Infinity-Instruct).
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<img src="fig/trainingflow.png">
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</p>
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Infinity-Instruct-7M-
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```bash
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epoch: 3
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## **How to use**
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Infinity-Instruct-7M-
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```bash
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<|im_start|>system
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import torch
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device = "cuda" # the device to load the model onto
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model = AutoModelForCausalLM.from_pretrained("BAAI/Infinity-Instruct-7M-
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torch_dtype=torch.bfloat16,
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device_map="auto"
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)
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tokenizer = AutoTokenizer.from_pretrained("BAAI/Infinity-Instruct-7M-
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# This template is copied from OpenHermers-mistral-2.5 (https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B)
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prompt = "Give me a short introduction to large language model."
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<em>[Paper][Code][π€] (would be released soon)</em>
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</p>
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Infinity-Instruct-7M-Gen-Mistral-7B 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](https://huggingface.co/datasets/BAAI/Infinity-Instruct) and showing favorable results on AlpacaEval 2.0 compared to Mixtral 8x22B v0.1, Gemini Pro, and GPT-4.
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## **News**
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- π₯π₯π₯[2024/08/02] We release the model weights of [InfInstruct-Llama3.1-70B Gen](https://huggingface.co/BAAI/Infinity-Instruct-7M-Gen-Llama3_1-70B), [InfInstruct-Llama3.1-8B Gen](https://huggingface.co/BAAI/Infinity-Instruct-7M-Gen-Llama3_1-70B), [InfInstruct-Mistral-7B Gen](https://huggingface.co/BAAI/Infinity-Instruct-7M-Gen-Mistral-7B).
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- π₯π₯π₯[2024/08/02] We release the 7M foundational dataset [Infinity-Instruct-7M](https://huggingface.co/datasets/BAAI/Infinity-Instruct).
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<img src="fig/trainingflow.png">
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</p>
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Infinity-Instruct-7M-Gen-Mistral-7B is tuned on Million-level instruction dataset [Infinity-Instruct](https://huggingface.co/datasets/BAAI/Infinity-Instruct). First, we apply the foundational dataset Infinity-Instruct-7M to improve the foundational ability (math & code) of Mistral-7B-v0.1, and get the foundational instruct model Infinity-Instruct-7M-Mistral-7B. Then we finetune the Infinity-Instruct-7M-Mistral-7B to get the stronger chat model Infinity-Instruct-7M-Gen-Mistral-7B. Here is the training hyperparamers.
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```bash
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epoch: 3
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## **How to use**
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Infinity-Instruct-7M-Gen-Mistral-7B adopt the same chat template of [OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B):
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```bash
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<|im_start|>system
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import torch
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device = "cuda" # the device to load the model onto
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model = AutoModelForCausalLM.from_pretrained("BAAI/Infinity-Instruct-7M-Gen-Mistral-7B",
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torch_dtype=torch.bfloat16,
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device_map="auto"
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)
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tokenizer = AutoTokenizer.from_pretrained("BAAI/Infinity-Instruct-7M-Gen-Mistral-7BB")
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# This template is copied from OpenHermers-mistral-2.5 (https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B)
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prompt = "Give me a short introduction to large language model."
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