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:
- 62ce64fc336c1499b40350b7a13aa6c8a2deed72a2d3da531ac605723457cc4c
- Size of remote file:
- 366 kB
- SHA256:
- d31b5191df6c4f7e152116783553197a5c731a02049f5a339f228b4f54cfafef
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