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:
- 403c9d33e986ee2bf08396bfaa9804976641dff4bfabdd689864d8931915202f
- Size of remote file:
- 4.64 MB
- SHA256:
- ffe2454126aa0e4072b74a4d729440b30467a452c4374cd8701c2ca1877d101f
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