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-14B-Preview
pipeline_tag: text-generation
tags:
- mlx
mlx-community/DeepCoder-14B-Preview-8bit
This model mlx-community/DeepCoder-14B-Preview-8bit was converted to MLX format from agentica-org/DeepCoder-14B-Preview using mlx-lm version 0.22.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/DeepCoder-14B-Preview-8bit")
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)