mlx-community/magnum-v2-72b-4bit
The Model mlx-community/magnum-v2-72b-4bit was converted to MLX format from anthracite-org/magnum-v2-72b using mlx-lm version 0.20.4.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/magnum-v2-72b-4bit")
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)
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Model tree for mlx-community/magnum-v2-72b-4bit
Datasets used to train mlx-community/magnum-v2-72b-4bit
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