metadata
library_name: mlx
license: mit
pipeline_tag: text-generation
tags:
- mlx
base_model:
- inclusionAI/Ling-1T
mlx-community/Ling-1T-mlx-3bit/
This model mlx-community/Ling-1T-mlx-3bit/ was converted to MLX format from inclusionAI/Ling-1T using mlx-lm version 0.28.1.
You can find more similar MLX model quants for Apple Mac Studio with 512 GB at https://huggingface.co/bibproj
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/Ling-1T-mlx-3bit/")
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)