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README.md
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---
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license: other
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license_name: tongyi-qianwen
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license_link: https://huggingface.co/Qwen/Qwen2-72B-Instruct/blob/main/LICENSE
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language:
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- en
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- zh
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pipeline_tag: text-generation
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tags:
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- chat
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---
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## This repo contains EXL2 quants of the model. If you need the original weights, please find them [here](https://huggingface.co/anthracite-org/magnum-32b-v1).
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## Base repo only contains the measurement file, see revisions for your quant of choice.
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This is the second in a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet and Opus. This model is fine-tuned on top of [Qwen1.5 32B](https://huggingface.co/Qwen/Qwen1.5-32B).
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## Prompting
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Model has been Instruct tuned with the ChatML formatting. A typical input would look like this:
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```py
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"""<|im_start|>user
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Hi there!<|im_end|>
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<|im_start|>assistant
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Nice to meet you!<|im_end|>
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<|im_start|>user
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Can I ask a question?<|im_end|>
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<|im_start|>assistant
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"""
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```
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## Credits
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Three new general purpose instruction following datasets were added on top of the original Stheno dataset (which had certain low quality entries purged/removed).
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The first two were designed specifically for the Magnum series, to better address prompt adherence and coherence:
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- [kalomaze/Opus_Instruct_25k](https://huggingface.co/datasets/kalomaze/Opus_Instruct_25k)
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- [Nopm/Opus_WritingStruct](https://huggingface.co/datasets/Nopm/Opus_WritingStruct)
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- [Gryphe/Sonnet3.5-SlimOrcaDedupCleaned](https://huggingface.co/datasets/Gryphe/Sonnet3.5-SlimOrcaDedupCleaned) (A ~16k rows subset)
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This model has been a team effort, and the credits goes to all members of Anthracite.
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## Training
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The training was done for 2 epochs with a learning rate of 1e-05. We used 8x [NVIDIA H100 Tensor Core](https://www.nvidia.com/en-us/data-center/h100/) GPUs for the full-parameter fine-tuning of the model.
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
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## Safety
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...
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