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
Upload config.json with huggingface_hub
Browse files- config.json +2 -2
config.json
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"audio_pool_step": 2,
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"auto_map": {
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"AutoConfig": "configuration_minicpm.MiniCPMOConfig",
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"AutoModel": "
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"AutoModelForCausalLM": "
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},
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"batch_vision_input": true,
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"bos_token_id": 151643,
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"audio_pool_step": 2,
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"auto_map": {
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"AutoConfig": "configuration_minicpm.MiniCPMOConfig",
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"AutoModel": "M-Ziyo/tiny-random-MiniCPM-o-2_6-mini--modeling_minicpmo.MiniCPMO",
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"AutoModelForCausalLM": "M-Ziyo/tiny-random-MiniCPM-o-2_6-mini--modeling_minicpmo.MiniCPMO"
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},
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"batch_vision_input": true,
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"bos_token_id": 151643,
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