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:
- d4239feb611bb1f7f275c7035c0a80ba99288912af391bf0c7b54b27b7bad3c4
- Size of remote file:
- 2.42 MB
- SHA256:
- 1c94c7e6594c6e0433114f54d6622dfe748e13fe2790caf21f7ca1751849c3e0
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