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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ef74483259d289315f3448f5e7435d0a066f343211903e105a32411a0d773e9
- Size of remote file:
- 56.7 MB
- SHA256:
- b4fa9f42bf917a7ad3ca34776d73908eed8a94948eff9ac237eaf8b804614be2
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