--- language: - en - fr - de - es - it - pt - ru - zh - ja license: other tags: - chat base_model: Qwen/Qwen2-72B-Instruct datasets: - Doctor-Shotgun/C2-Stheno - anthracite-org/kalo-opus-instruct-22k-no-refusal - anthracite-org/nopm_claude_writing_fixed license_name: tongyi-qianwen license_link: https://huggingface.co/anthracite-org/magnum-v2-72b/blob/main/LICENSE pipeline_tag: text-generation model-index: - name: magnum-v2-72b results: - task: type: text-generation name: Text Generation dataset: name: IFEval (0-Shot) type: HuggingFaceH4/ifeval args: num_few_shot: 0 metrics: - type: inst_level_strict_acc and prompt_level_strict_acc value: 75.6 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v2-72b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: BBH (3-Shot) type: BBH args: num_few_shot: 3 metrics: - type: acc_norm value: 57.85 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v2-72b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: hendrycks/competition_math args: num_few_shot: 4 metrics: - type: exact_match value: 31.65 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v2-72b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa args: num_few_shot: 0 metrics: - type: acc_norm value: 18.12 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v2-72b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MuSR (0-shot) type: TAUR-Lab/MuSR args: num_few_shot: 0 metrics: - type: acc_norm value: 14.18 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v2-72b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU-PRO (5-shot) type: TIGER-Lab/MMLU-Pro config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 49.51 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v2-72b name: Open LLM Leaderboard --- # MLX Format and Quantizations for Magnum v2 72b Quantized to 4 bpw precision and tested using the `mlx_lm` utility on a 64GiB URAM M1 Max. See [original model](https://huggingface.co/anthracite-org/magnum-v2-72b) for further details. Larger, 8bpw quants available at [mlx-community](https://huggingface.co/mlx-community/magnum-v2-72b). # Original Model card ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6491e00e057b0928b3e07b75/u8B-5bEeroN549uxUIisV.png) This is the seventh (Lucky!) 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 [Qwen-2 72B Instruct](https://huggingface.co/Qwen/Qwen2-72B-Instruct). ## Prompting Model has been Instruct tuned with the ChatML formatting. A typical input would look like this: ```py """<|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 - [anthracite-org/Stheno-Data-Filtered](https://huggingface.co/datasets/anthracite-org/Stheno-Data-Filtered) - [anthracite-org/kalo-opus-instruct-22k-no-refusal](https://huggingface.co/datasets/anthracite-org/kalo-opus-instruct-22k-no-refusal) - [anthracite-org/nopm_claude_writing_fixed](https://huggingface.co/datasets/anthracite-org/nopm_claude_writing_fixed) 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 [AMD Instinct™ MI300X Accelerators](https://www.amd.com/en/products/accelerators/instinct/mi300/mi300x.html) for the full-parameter fine-tuning of the model. We also trained with a weight decay of 0.01 to help further stabilize the loss trajectory and mitigate catastrophic forgetting, and utilize a peak learning rate of 4e-6 to prevent the 2nd epoch loss from dropping too significantly (as it is a strong indicator of overfitting). ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6491e00e057b0928b3e07b75/hVd5gNqSLOlWTkUb0A7iE.png) Sample Packing was done for 16k tokens rather than the 8k tokens used in our previous runs. [Built with Axolotl](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-v2-72b) | Metric |Value| |-------------------|----:| |Avg. |41.15| |IFEval (0-Shot) |75.60| |BBH (3-Shot) |57.85| |MATH Lvl 5 (4-Shot)|31.65| |GPQA (0-shot) |18.12| |MuSR (0-shot) |14.18| |MMLU-PRO (5-shot) |49.51| # [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-v2-72b) | Metric |Value| |-------------------|----:| |Avg. |41.15| |IFEval (0-Shot) |75.60| |BBH (3-Shot) |57.85| |MATH Lvl 5 (4-Shot)|31.65| |GPQA (0-shot) |18.12| |MuSR (0-shot) |14.18| |MMLU-PRO (5-shot) |49.51|