isv2lf/magnum-v4-22b-Q4-mlx
The Model isv2lf/magnum-v4-22b-Q4-mlx was converted to MLX format from anthracite-org/magnum-v4-22b using mlx-lm version 0.20.5.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("isv2lf/magnum-v4-22b-Q4-mlx")
prompt="hello"
if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
- Downloads last month
- 23
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
Model tree for isv2lf/magnum-v4-22b-Q4-mlx
Base model
anthracite-org/magnum-v4-22bDatasets used to train isv2lf/magnum-v4-22b-Q4-mlx
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