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:
- 6b9d2af4c4296c391d8e92aa070812ba65f68a878d295f822f44152e7fc8da1d
- Size of remote file:
- 33.6 MB
- SHA256:
- 464c98f0fda7d442bae665fcfce9b00bea2a2229ca3c953b966f394d763e3e85
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