Instructions to use hf-internal-testing/tiny-random-PatchTSMixerModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PatchTSMixerModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-PatchTSMixerModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-PatchTSMixerModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-PatchTSMixerModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1603aa635cd3bd2ad7d7c29e782279d066e5388efeb8a8048aa21f4f9b2c67cf
- Size of remote file:
- 136 kB
- SHA256:
- d9e140b54c687044445dbf1df6c8a1c6de207d936b97310e2deb071b1d6f8302
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