Instructions to use mlx-community/Octopus-v2-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Octopus-v2-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Octopus-v2-4bit mlx-community/Octopus-v2-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
mlx-community/Octopus-v2-4bit
This model was converted to MLX format from NexaAIDev/Octopus-v2 using mlx-lm version 0.7.0.
Refer to the original model card for more details on the model.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/Octopus-v2-4bit")
response = generate(model, tokenizer, prompt="hello", verbose=True)
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Model tree for mlx-community/Octopus-v2-4bit
Base model
google/gemma-2b
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Octopus-v2-4bit mlx-community/Octopus-v2-4bit