Any-to-Any
Transformers
Safetensors
MLX
minicpmo
feature-extraction
minicpm-o
minicpm-v
multimodal
full-duplex
custom_code
4-bit precision
Instructions to use mlx-community/MiniCPM-o-4_5-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlx-community/MiniCPM-o-4_5-4bit with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mlx-community/MiniCPM-o-4_5-4bit", trust_remote_code=True, device_map="auto") - MLX
How to use mlx-community/MiniCPM-o-4_5-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download mlx-community/MiniCPM-o-4_5-4bit --local-dir MiniCPM-o-4_5-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download model-00001-of-00002.safetensors from mlx-community/MiniCPM-o-4_5-4bit: direct link, hf CLI and curl.
- Browser
- Download file 5.36 GB
-
https://huggingface.co/mlx-community/MiniCPM-o-4_5-4bit/resolve/main/model-00001-of-00002.safetensors
- Command line
-
hf download hf://mlx-community/MiniCPM-o-4_5-4bit/model-00001-of-00002.safetensors
-
curl -L -o model-00001-of-00002.safetensors https://huggingface.co/mlx-community/MiniCPM-o-4_5-4bit/resolve/main/model-00001-of-00002.safetensors
5.36 GB
- Xet hash:
- ddf5f53b43f499adfe4ac66564bcb1d43088866b1125de06dd348545ff30723c
- Size of remote file:
- 5.36 GB
- SHA256:
- f90098983cc0aa9ebbe229df10c3de352f33a07ef57c321e76437bab5fa5a2c7
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