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metadata
license: llama3.1
language:
  - en
pipeline_tag: text-generation
datasets:
  - allenai/RLVR-GSM-MATH-IF-Mixed-Constraints
base_model: allenai/Llama-3.1-Tulu-3-8B
library_name: transformers
tags:
  - mlx

mlx-community/Llama-3.1-Tulu-3-8B-4bit

The Model mlx-community/Llama-3.1-Tulu-3-8B-4bit was converted to MLX format from allenai/Llama-3.1-Tulu-3-8B using mlx-lm version 0.20.0.

Use with mlx

pip install mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("mlx-community/Llama-3.1-Tulu-3-8B-4bit")

prompt="hello"

if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, tokenize=False, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)