metadata

license: mit
language:
  - en
base_model: microsoft/NextCoder-32B
pipeline_tag: text-generation
library_name: mlx
tags:
  - code
  - chat
  - microsoft
  - nextcoder
  - selekt
  - mlx
datasets:
  - microsoft/NextCoderDataset
  - microsoft/NextCoderDataset-Conversational
  - bigcode/commitpackft
  - bigcode/starcoderdata

jedisct1/NextCoder-32B-q8-mlx

This model jedisct1/NextCoder-32B-q8-mlx was converted to MLX format from microsoft/NextCoder-32B using mlx-lm version 0.25.3.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("jedisct1/NextCoder-32B-q8-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)