mlx-community/Marx-3B-V2-6bit
The Model mlx-community/Marx-3B-V2-6bit was converted to MLX format from acrastt/Marx-3B-V2 using mlx-lm version 0.22.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/Marx-3B-V2-6bit")
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/Marx-3B-V2-6bit
Base model
acrastt/Marx-3B-V2Dataset used to train mlx-community/Marx-3B-V2-6bit
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard44.030
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard72.920
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard27.840
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard39.920
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard66.540
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard1.210