djuna/MN-Chinofun-12B-4-4bit
The Model djuna/MN-Chinofun-12B-4-4bit was converted to MLX format from djuna/MN-Chinofun-12B-4 using mlx-lm version 0.21.5.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("djuna/MN-Chinofun-12B-4-4bit")
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)
- Downloads last month
- 3
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
Model tree for djuna/MN-Chinofun-12B-4-4bit
Base model
djuna/MN-Chinofun-12B-4Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard54.040
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard34.170
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard10.350
- acc_norm on GPQA (0-shot)Open LLM Leaderboard6.040
- acc_norm on MuSR (0-shot)Open LLM Leaderboard13.230
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard27.750