Add pipeline tag, library name, and links to paper and code
#2
by nielsr HF Staff - opened
README.md
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@@ -1,10 +1,13 @@
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---
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license: apache-2.0
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datasets:
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- BAAI/Infinity-Instruct
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language:
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- en
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---
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# Infinity Instruct
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<p align="center">
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@@ -12,7 +15,7 @@ language:
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</p>
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<p align="center">
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<em>Beijing Academy of Artificial Intelligence (BAAI)</em><br/>
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<em>[Paper][Code][🤗] (would be released soon)</em>
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</p>
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Infinity-Instruct-3M-0625-Llama3-8B 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](https://huggingface.co/datasets/BAAI/Infinity-Instruct) and showing favorable results on AlpacaEval 2.0 and MT-Bench.
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@@ -143,6 +146,4 @@ Our paper, detailing the development and features of the **Infinity Instruct** d
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journal={arXiv preprint arXiv:2406.XXXX},
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year={2024}
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}
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```
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-
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-
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---
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datasets:
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- BAAI/Infinity-Instruct
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language:
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- en
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license: apache-2.0
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pipeline_tag: text-generation
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library_name: transformers
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---
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# Infinity Instruct
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<p align="center">
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</p>
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<p align="center">
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<em>Beijing Academy of Artificial Intelligence (BAAI)</em><br/>
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<em>[Paper](https://huggingface.co/papers/2506.11116)[Code](https://github.com/FlagOpen/FlagScale)[🤗] (would be released soon)</em>
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</p>
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Infinity-Instruct-3M-0625-Llama3-8B 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](https://huggingface.co/datasets/BAAI/Infinity-Instruct) and showing favorable results on AlpacaEval 2.0 and MT-Bench.
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journal={arXiv preprint arXiv:2406.XXXX},
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year={2024}
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}
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```
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