metadata
datasets:
- PowerInfer/QWQ-LONGCOT-500K
- PowerInfer/LONGCOT-Refine-500K
base_model: PowerInfer/SmallThinker-3B-Preview
pipeline_tag: text-generation
language:
- en
library_name: transformers
tags:
- mlx
mlx-community/smallthinker-3b-preview-q8
The Model mlx-community/smallthinker-3b-preview-q8 was converted to MLX format from PowerInfer/SmallThinker-3B-Preview using mlx-lm version 0.20.5.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/smallthinker-3b-preview-q8")
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)