metadata

license: mit
datasets:
  - SWE-Gym/SWE-Gym
language:
  - en
base_model: all-hands/openhands-lm-32b-v0.1
pipeline_tag: text-generation
tags:
  - agent
  - coding
  - mlx
library_name: mlx

mlx-community/openhands-lm-32b-v0.1-4bit

This model mlx-community/openhands-lm-32b-v0.1-4bit was converted to MLX format from all-hands/openhands-lm-32b-v0.1 using mlx-lm version 0.22.2.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("mlx-community/openhands-lm-32b-v0.1-4bit")

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)