metadata
base_model: togethercomputer/Tev1-4B-experimental
pipeline_tag: text-generation
library_name: mlx
tags:
- together-ai
- qwen3.5
- decision-model
- experimental
- mlx
gavinmroy/Tev1-4B-experimental-mlx-4bit
This model gavinmroy/Tev1-4B-experimental-mlx-4bit was converted to MLX format from togethercomputer/Tev1-4B-experimental using mlx-lm version 0.31.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("gavinmroy/Tev1-4B-experimental-mlx-4bit")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True, return_dict=False,
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)