metadata
license: llama3.1
library_name: transformers
base_model: deepcogito/cogito-v2-preview-llama-70B
pipeline_tag: text-generation
tags:
- mlx
Basher17/cogito-v2-preview-llama-70B-mlx-4Bit
The Model mlx-community/cogito-v2-preview-llama-70B-mlx-4Bit was converted to MLX format from deepcogito/cogito-v2-preview-llama-70B using mlx-lm version 0.22.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/cogito-v2-preview-llama-70B-mlx-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)