Quantization made by Richard Erkhov.
Qwen2.5-Coder-0.5B-Instruct-MLX - GGUF
- Model creator: https://huggingface.co/TheBlueObserver/
- Original model: https://huggingface.co/TheBlueObserver/Qwen2.5-Coder-0.5B-Instruct-MLX/
Original model description:
license: apache-2.0 license_link: https://huggingface.co/Qwen/Qwen2.5-Coder-0.5B-Instruct/blob/main/LICENSE language: - en base_model: Qwen/Qwen2.5-Coder-0.5B-Instruct pipeline_tag: text-generation library_name: transformers tags: - code - codeqwen - chat - qwen - qwen-coder - mlx
TheBlueObserver/Qwen2.5-Coder-0.5B-Instruct-MLX
The Model TheBlueObserver/Qwen2.5-Coder-0.5B-Instruct-MLX was converted to MLX format from Qwen/Qwen2.5-Coder-0.5B-Instruct using mlx-lm version 0.20.2.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("TheBlueObserver/Qwen2.5-Coder-0.5B-Instruct-MLX")
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)