Instructions to use hf-internal-testing/tiny-random-YosoModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-YosoModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-YosoModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-YosoModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-YosoModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e887503a8dca7ab184dedd7f4f6a73a3698f9b56ec4ed85f032f6b858e3a6865
- Size of remote file:
- 348 kB
- SHA256:
- 4880e736705002ecf67259188cf745a1b13126b8dde2961581ada7d823ad4577
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