metadata
license: mit
library_name: mlx
pipeline_tag: text-generation
base_model: ByteDance-Seed/Seed-Coder-8B-Base
tags:
- mlx
Seed-Coder-8B-Base-DWQ
This model Seed-Coder-8B-Base-DWQ was converted to MLX format from Seed-Coder-8B-Base.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("TechxGenus/Seed-Coder-8B-Base-DWQ")
prompt = "def quick_sort(arr):"
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)