This is 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-Small-Instruct-2409.
Prompting
A typical input would look like this:
<s>[INST] SYSTEM MESSAGE
USER MESSAGE[/INST] ASSISTANT MESSAGE</s>[INST] USER MESSAGE[/INST]
SillyTavern templates
Below are Instruct and Context templates for use within SillyTavern.
Axolotl config
Credits
We'd like to thank Recursal / Featherless for sponsoring the compute for this train, Featherless has been hosting our Magnum models since the first 72 B and has given thousands of people access to our models and helped us grow.
We would also like to thank all members of Anthracite who made this finetune possible.
Datasets
- anthracite-org/c2_logs_32k_mistral-v3_v1.2_no_system
- anthracite-org/kalo-opus-instruct-22k-no-refusal-no-system
- anthracite-org/kalo-opus-instruct-3k-filtered-no-system
- anthracite-org/nopm_claude_writing_fixed
- anthracite-org/kalo_opus_misc_240827_no_system
- anthracite-org/kalo_misc_part2_no_system
Training
The training was done for 2 epochs. We used 8xH100s GPUs graciously provided by Recursal AI / Featherless AI for the full-parameter fine-tuning of the model.
Safety
...
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 27.45 |
| IFEval (0-Shot) | 56.29 |
| BBH (3-Shot) | 35.55 |
| MATH Lvl 5 (4-Shot) | 17.60 |
| GPQA (0-shot) | 10.40 |
| MuSR (0-shot) | 13.43 |
| MMLU-PRO (5-shot) | 31.44 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard56.290
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard35.550
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard17.600
- acc_norm on GPQA (0-shot)Open LLM Leaderboard10.400
- acc_norm on MuSR (0-shot)Open LLM Leaderboard13.430
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard31.440
