Any-to-Any
Transformers
ONNX
Safetensors
minicpmo
feature-extraction
minicpm-o
minicpm-v
multimodal
full-duplex
custom_code
Instructions to use rycerzes/MiniCPM-o-4_5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rycerzes/MiniCPM-o-4_5 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rycerzes/MiniCPM-o-4_5", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from rycerzes/MiniCPM-o-4_5: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/rycerzes/MiniCPM-o-4_5/resolve/main/tokenizer.json
- Command line
-
hf download hf://rycerzes/MiniCPM-o-4_5/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/rycerzes/MiniCPM-o-4_5/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- b31462544c7f9d3d986c4ea344d7ed3082a8a77417f0906cf3f05fbd0eabdb30
- Size of remote file:
- 11.4 MB
- SHA256:
- 6d55eb34389b8c87403763cc1d80447d91c85c7cd39cd5e3c0dc2d49edad989d
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