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:
- 6de5a15a3c2c3df8f9453116db00c28a627ff6c1c56f7b8417d934921e7525fb
- Size of remote file:
- 4.64 MB
- SHA256:
- e23e79ef77081ed1fffe649febfba7e1e3e67fd2f50cc102ec51295587727ca8
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