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:
- c09bb7af375b342565769d608fda3e579698ac13629803bcf4d0b32514a7792f
- Size of remote file:
- 430 kB
- SHA256:
- cc8cb86cf7a1f195ed3e4b8d24f079331450f23cef1ba2293b588e3525a794d9
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