metadata
license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen2.5-14B-Instruct-1M/blob/main/LICENSE
language:
- en
pipeline_tag: text-generation
base_model: mlx-community/Qwen2.5-14B-Instruct-1M-8bit
tags:
- chat
- mlx
library_name: mlx
parole-study-viper/speech-to-sql
This model parole-study-viper/speech-to-sql was converted to MLX format from mlx-community/Qwen2.5-14B-Instruct-1M-8bit using mlx-lm version 0.23.2.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("parole-study-viper/speech-to-sql")
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)