Instructions to use hf-internal-testing/tiny-random-PersimmonModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PersimmonModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-PersimmonModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-PersimmonModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-PersimmonModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 223732e34f54b2321ede5f1fd5823fdc5268fe47d0b78fc9c0d1a79b3936adfa
- Size of remote file:
- 33.6 MB
- SHA256:
- 773cc39b7a01c8ff8f1e0d311ade366dbf202129d18e2c62f8a146318728ee19
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