metadata
license: apache-2.0
language:
- en
base_model: Suu/Klear-Reasoner-8B
datasets:
- Suu/KlearReasoner-MathSub-30K
- Suu/KlearReasoner-CodeSub-15K
metrics:
- accuracy
tags:
- mlx
hobaratio/Klear-Reasoner-8B-mlx-8Bit
The Model hobaratio/Klear-Reasoner-8B-mlx-8Bit was converted to MLX format from Suu/Klear-Reasoner-8B using mlx-lm version 0.26.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("hobaratio/Klear-Reasoner-8B-mlx-8Bit")
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)