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:
- 891242dd3bba3756d0c0a5ad8985b2795d77aa0a036ede533953212138ed8955
- Size of remote file:
- 253 kB
- SHA256:
- dc26d0e4e05545db21c58a9055f7d9da4b006c824d47c5b98329fa56f0aa72e5
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