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:
- 7157db6649e0f28b9829916466053c3a9ba277b24ae4876f596314f5b4679fc5
- Size of remote file:
- 136 kB
- SHA256:
- a9ca1caed024907812b20f34b911521c69d42d60f3b37d6dae9130b63acda5e8
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