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:
- 97fbf67495324791c6f027a51c121ba78423667f430d847b5e8d996de589defd
- Size of remote file:
- 33.6 MB
- SHA256:
- 6d49a7172407914867c3980414ef7c3c0e25ac2e5dfd1c2275d42a26df6be4fe
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