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:
- 824a54f0ffa258b85a7e2ea26350e154d2368f4348a04ab7cb1330b51e6c5f10
- Size of remote file:
- 4.64 MB
- SHA256:
- 670900b2d0a345522527f211de525c1ca832018c2d74cec6243fae0cb39ad70c
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