mlx-community/SuperNova-Medius-4bit
The Model mlx-community/SuperNova-Medius-4bit was converted to MLX format from arcee-ai/SuperNova-Medius using mlx-lm version 0.19.0.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/SuperNova-Medius-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
- 48
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for mlx-community/SuperNova-Medius-4bit
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard55.600
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard49.300
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard32.480
- acc_norm on GPQA (0-shot)Open LLM Leaderboard17.900
- acc_norm on MuSR (0-shot)Open LLM Leaderboard19.190
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard48.830