metadata
library_name: transformers
model_name: shisa-v2-llama3.3-70b
license: llama3.3
datasets:
- shisa-ai/shisa-v2-sharegpt
- shisa-ai/deepseekv3-ultrafeedback-armorm-dpo
language:
- ja
- en
base_model: shisa-ai/shisa-v2-llama3.3-70b
pipeline_tag: text-generation
tags:
- mlx
mlx-community/shisa-v2-llama3.3-70b-mlx-fp16
The Model mlx-community/shisa-v2-llama3.3-70b-mlx-bf16 was converted to MLX format from shisa-ai/shisa-v2-llama3.3-70b using mlx-lm version 0.22.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("bibproj/shisa-v2-llama3.3-70b-mlx-fp16")
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)