metadata
base_model: gradientai/Llama-3-8B-Instruct-Gradient-4194k
language:
- en
license: llama3
pipeline_tag: text-generation
tags:
- meta
- llama-3
- mlx
mlx-community/gradientai_Llama-3-8B-Instruct-Gradient-4194k_4bit
The Model mlx-community/gradientai_Llama-3-8B-Instruct-Gradient-4194k_4bit was converted to MLX format from gradientai/Llama-3-8B-Instruct-Gradient-4194k using mlx-lm version 0.19.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/gradientai_Llama-3-8B-Instruct-Gradient-4194k_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)