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:
- 8e469163f7a9ce760567cc063b8e07caa1fdc4a58abc657886a95986637826bd
- Size of remote file:
- 33.6 MB
- SHA256:
- 7ee41cc332b88e4551c3e920708f33d6211c234b072e09854c5d6a53c61ab0a6
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