metadata
library_name: mlx
inference: false
extra_gated_description: >-
To learn more about how we process your personal data, please read our <a
href="https://poolside.ai/legal/privacy">Privacy Policy</a>.
tags:
- laguna-xs.2
- mlx
license: apache-2.0
pipeline_tag: text-generation
base_model: poolside/Laguna-XS.2
mlx-community/Laguna-XS.2-4bit
This model mlx-community/Laguna-XS.2-4bit was converted to MLX format from poolside/Laguna-XS.2 using mlx-lm version 0.31.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/Laguna-XS.2-4bit")
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)