Instructions to use hf-internal-testing/tiny-random-longformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-longformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-longformer")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-longformer") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-longformer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7fa5c456a17ed0bcbd95e35620c668500bbd69f710e5cee6521bd6150608700
- Size of remote file:
- 586 kB
- SHA256:
- 02b21b426183b4189455af54deb4243b81be8cb454879a6df295303ee8bea295
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