Instructions to use hf-internal-testing/tiny-random-PatchTSTModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PatchTSTModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-PatchTSTModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-PatchTSTModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-PatchTSTModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d88b9ad813ff48b74d15003d512ac7e34f3d886b285d445c1d886062f78fd486
- Size of remote file:
- 453 kB
- SHA256:
- ea563f4db77ecec54cb29ec2792686a1fc8c295fe0791a201dc728b88c27393e
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