Instructions to use Baicai003/tiny-clip-one with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Baicai003/tiny-clip-one with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Baicai003/tiny-clip-one")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("Baicai003/tiny-clip-one") model = AutoModel.from_pretrained("Baicai003/tiny-clip-one") - Notebooks
- Google Colab
- Kaggle
Upload config.json with huggingface_hub
Browse files- config.json +1 -1
config.json
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"attention_probs_dropout_prob": 0.1,
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"context_length": 1,
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"architectures": [
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"CLIPTextModel"
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"attention_probs_dropout_prob": 0.1,
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"context_length": 1,
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