Text Generation
Safetensors
qwen2
chat
conversational
Eval Results
4-bit precision
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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

image/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.

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

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). image/png

Sample Packing was done for 16k tokens rather than the 8k tokens used in our previous runs.

Built with Axolotl

Safety

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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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