metadata
language:
- en
metrics:
- accuracy
base_model: Menlo/ReZero-v0.1-llama-3.2-3b-it-grpo-250404
pipeline_tag: text-generation
tags:
- mlx
library_name: mlx
mlx-community/ReZero-v0.1-llama-3.2-3b-it-grpo-250404-8bit
This model mlx-community/ReZero-v0.1-llama-3.2-3b-it-grpo-250404-8bit was converted to MLX format from Menlo/ReZero-v0.1-llama-3.2-3b-it-grpo-250404 using mlx-lm version 0.22.5.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/ReZero-v0.1-llama-3.2-3b-it-grpo-250404-8bit")
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)