metadata
license: mit
datasets:
- cheapresearch/CheapResearch-DS-33k
tags:
- mlx
base_model: cheapresearch/CheapResearch-4B-Thinking
library_name: mlx
pipeline_tag: text-generation
Otilde/CheapResearch-4B-Thinking-MXFP4-MLX
This model Otilde/CheapResearch-4B-Thinking-MXFP4-MLX was converted to MLX format from cheapresearch/CheapResearch-4B-Thinking using mlx-lm version 0.28.2.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("Otilde/CheapResearch-4B-Thinking-MXFP4-MLX")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)