Instructions to use hf-tiny-model-private/tiny-random-YosoModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-YosoModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-YosoModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-YosoModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-YosoModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0334456ec29304d0670057b747a513f744de447d955a5e598541f66589003fe
- Size of remote file:
- 366 kB
- SHA256:
- 64400d1e7a47251d818ea2503424912e050870c9f73659450d61c5610900abe0
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