![image/png](https://cdn-uploads.huggingface.co/production/uploads/658a46cbfb9c2bdfae75b3a6/A9n8EJBDQziJWnXhOYeEE.png) This is the fourth 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 [Mistral-Nemo-Base-2407](https://huggingface.co/mistralai/Mistral-Nemo-Base-2407). ## Prompting Model has been Instruct tuned with the ChatML formatting. A typical input would look like this: ```py """<|im_start|>system system prompt<|im_end|> <|im_start|>user Hi there!<|im_end|> <|im_start|>assistant Nice to meet you!<|im_end|> <|im_start|>user Can I ask a question?<|im_end|> <|im_start|>assistant """ ``` ## Credits - Stheno dataset (filtered) - [kalomaze/Opus_Instruct_25k](https://huggingface.co/datasets/kalomaze/Opus_Instruct_25k) - [Nopm/Opus_WritingStruct](https://huggingface.co/datasets/Nopm/Opus_WritingStruct) - [Gryphe/Sonnet3.5-SlimOrcaDedupCleaned](https://huggingface.co/datasets/Gryphe/Sonnet3.5-SlimOrcaDedupCleaned) (A ~16k rows subset) - [kalomaze/Opus_Instruct_3k](https://huggingface.co/datasets/kalomaze/Opus_Instruct_3k) This model has been a team effort, and the credits goes to all members of Anthracite. ## Training The training was done for 2 epochs. 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. [

](https://github.com/OpenAccess-AI-Collective/axolotl) ## Safety ... # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_anthracite-org__magnum-v2-12b) | Metric |Value| |-------------------|----:| |Avg. |18.68| |IFEval (0-Shot) |37.62| |BBH (3-Shot) |28.79| |MATH Lvl 5 (4-Shot)| 4.76| |GPQA (0-shot) | 5.48| |MuSR (0-shot) |11.37| |MMLU-PRO (5-shot) |24.08|