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:
- e42c4a1a46d36545ff0d472f0cec8eb277f0c505549c0a22dc91c42bc3d4fdb8
- Size of remote file:
- 749 kB
- SHA256:
- 893556271530d10f90838549a20a2d65bd48e3d28f4623204025075f09182e25
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