metadata
license: apache-2.0
pipeline_tag: text-generation
library_name: mlx
datasets:
- Alibaba-Apsara/Superior-Reasoning-SFT-gpt-oss-120b
- Alibaba-Apsara/Superior-Reasoning-SFT-gpt-oss-120b-Logprob
base_model: Alibaba-Apsara/DASD-4B-Thinking
tags:
- mlx
mlx-community/DASD-4B-Thinking-bfloat16
This model mlx-community/DASD-4B-Thinking-bfloat16 was converted to MLX format from Alibaba-Apsara/DASD-4B-Thinking using mlx-lm version 0.30.6.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/DASD-4B-Thinking-bfloat16")
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)