README.md

metadata

license: cc-by-sa-4.0
metrics:
  - accuracy
pipeline_tag: text-generation
tags:
  - code
  - mlx
  - mlx-my-repo
base_model: defog/llama-3-sqlcoder-8b

qdtomassi/llama-3-sqlcoder-8b-mlx-4Bit

The Model qdtomassi/llama-3-sqlcoder-8b-mlx-4Bit was converted to MLX format from defog/llama-3-sqlcoder-8b using mlx-lm version 0.22.3.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("qdtomassi/llama-3-sqlcoder-8b-mlx-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)