Image-to-Text
Transformers
Safetensors
minicpmo
feature-extraction
vision
multimodal
tiny-model
minicpm
custom_code
Instructions to use M-Ziyo/tiny-random-MiniCPM-o-2_6-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use M-Ziyo/tiny-random-MiniCPM-o-2_6-mini with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="M-Ziyo/tiny-random-MiniCPM-o-2_6-mini", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("M-Ziyo/tiny-random-MiniCPM-o-2_6-mini", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ca18c90f8c14781ba0960551fc75b7e4451a66efdcfd4a712285544f2df1d3ea
- Size of remote file:
- 11.4 MB
- SHA256:
- e43057e8380937b8edf2c9ea6ad34a3875d89c390e97024dfac307f3a4a11321
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