Instructions to use hf-internal-testing/tiny-random-IdeficsModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-IdeficsModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-IdeficsModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-IdeficsModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-IdeficsModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 33705208a2720180b6310a98c7a6538c2a1d1316cb83ad74b818c3d2343072ca
- Size of remote file:
- 4.64 MB
- SHA256:
- f6ab6a1fffafe0a16cbb1081a52c42e1320e13e5c069cb800597283eb94c7c84
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