metadata

base_model: amd/AMD-Llama-135m
datasets:
  - cerebras/SlimPajama-627B
  - manu/project_gutenberg
license: apache-2.0
tags:
  - mlx

mlx-community/AMD-Llama-135m-4bit

The Model mlx-community/AMD-Llama-135m-4bit was converted to MLX format from amd/AMD-Llama-135m using mlx-lm version 0.18.2.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("mlx-community/AMD-Llama-135m-4bit")

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)