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--- |
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License: apache-2.0 |
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Language: |
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- En |
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Pipeline_tag: text-generation |
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Base_model: IntervitensInc/Llama-3.1-Minitron-4B-Width-Base-chatml |
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tags: |
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- Chat |
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--- |
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## This repo contains GGUF quants of the model. If you need the original weights, please find them [here](https://huggingface.co/anthracite-org/magnum-v2-4b). |
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This is the eighth 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 [IntervitensInc/Llama-3.1-Minitron-4B-Width-Base-chatml](https://huggingface.co/IntervitensInc/Llama-3.1-Minitron-4B-Width-Base-chatml). |
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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|>system |
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system prompt<|im_end|> |
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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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## Support |
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In order to inference this model you will have to use Aphrodite or vLLM as llama.cpp has not yet merged the required pull request to fix llama3.1 rope_freqs not respecting custom head_dim - You can however get around this by quanting the model yourself with the following fixes for a working GGUF. However, it will be stuck at 8k context until [this PR](https://github.com/ggerganov/llama.cpp/pull/9141) is merged. |
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1. Remove `"rope_scaling": {}` from `config.json` |
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2. Change `"max_position_embeddings"` to `8192` in `config.json` |
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3. Add `"add_bos_token": false` to `tokenizer_config.json` |
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## Credits |
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- [anthracite-org/Stheno-Data-Filtered](https://huggingface.co/datasets/anthracite-org/Stheno-Data-Filtered) |
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- [anthracite-org/kalo-opus-instruct-22k-no-refusal](https://huggingface.co/datasets/anthracite-org/kalo-opus-instruct-22k-no-refusal) |
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- [lodrick-the-lafted/NopmWritingStruct](https://huggingface.co/datasets/lodrick-the-lafted/NopmWritingStruct) |
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- [NewEden/Gryphe-3.5-16k-Subset](NewEden/Gryphe-3.5-16k-Subset) |
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- [Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned](https://huggingface.co/datasets/Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned) |
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- [Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned](https://huggingface.co/datasets/Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned) |
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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. We used 2 x [RTX 6000s](https://store.nvidia.com/en-us/nvidia-rtx/products/nvidia-rtx-6000-ada-generation/) GPUs graciously provided by [Kubernetes_Bad](https://huggingface.co/kubernetes-bad) 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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... |
