metadata
base_model: Danau5tin/Orca-Agent-v0.1
license: apache-2.0
datasets:
- Danau5tin/terminal-tasks
tags:
- agent
- code
- multi-agent
- mlx
- mlx-my-repo
ncls-p/Orca-Agent-v0.1-mlx-4Bit
The Model ncls-p/Orca-Agent-v0.1-mlx-4Bit was converted to MLX format from Danau5tin/Orca-Agent-v0.1 using mlx-lm version 0.26.4.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("ncls-p/Orca-Agent-v0.1-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)