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:
- 5e34c60db4ab9693db01a7d942eaeeec6885407d66cb4e845b9ed971e8b813c6
- Size of remote file:
- 33.6 MB
- SHA256:
- 23178ee7b8b21530945f788299385f90d8152b00999dd9bb9b5f8a9dc7eafc2d
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