README.md

metadata

license: mit
library_name: mlx
datasets:
  - PrimeIntellect/verifiable-coding-problems
  - likaixin/TACO-verified
  - livecodebench/code_generation_lite
language:
  - en
base_model: agentica-org/DeepCoder-1.5B-Preview
pipeline_tag: text-generation
tags:
  - mlx

gingofthesouth/DeepCoder-1.5B-MLX

This model gingofthesouth/DeepCoder-1.5B-MLX was converted to MLX format from agentica-org/DeepCoder-1.5B-Preview using mlx-lm version 0.22.5.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("gingofthesouth/DeepCoder-1.5B-MLX")

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)