metadata
base_model: tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.1
datasets:
- lmsys/lmsys-chat-1m
- argilla/magpie-ultra-v0.1
language:
- en
- ja
library_name: transformers
license: llama3.1
pipeline_tag: text-generation
tags:
- mlx
model_type: llama
mlx-community/Llama-3.1-Swallow-8B-Instruct-v0.1-8bit
The Model mlx-community/Llama-3.1-Swallow-8B-Instruct-v0.1-8bit was converted to MLX format from tokyotech-llm/Llama-3.1-Swallow-8B-Instruct-v0.1 using mlx-lm version 0.19.0.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/Llama-3.1-Swallow-8B-Instruct-v0.1-8bit")
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)