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 for further details.
Larger, 8bpw quants available at mlx-community.
Original Model card
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.
Prompting
Model has been Instruct tuned with the ChatML formatting. A typical input would look like this:
"""<|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
- anthracite-org/kalo-opus-instruct-22k-no-refusal
- 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 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).
Sample Packing was done for 16k tokens rather than the 8k tokens used in our previous runs.
Safety
...
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
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
Detailed results can be found here
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 |
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Datasets used to train luigi86/magnum-v2-72b_mlx-4bpw
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard75.600
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard57.850
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard31.650
- acc_norm on GPQA (0-shot)Open LLM Leaderboard18.120
- acc_norm on MuSR (0-shot)Open LLM Leaderboard14.180
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard49.510