Instructions to use patrickvonplaten/longformer-random-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use patrickvonplaten/longformer-random-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="patrickvonplaten/longformer-random-tiny")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("patrickvonplaten/longformer-random-tiny") model = AutoModel.from_pretrained("patrickvonplaten/longformer-random-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from patrickvonplaten/longformer-random-tiny: direct link, hf CLI and curl.
- Browser
- Download file 22.3 kB
-
https://huggingface.co/patrickvonplaten/longformer-random-tiny/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://patrickvonplaten/longformer-random-tiny/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/patrickvonplaten/longformer-random-tiny/resolve/main/pytorch_model.bin
22.3 kB
- Xet hash:
- 58d6b7d62eebe87dac07cbbd0abe00dd03499c1000283fb9e02df5644c3e7009
- Size of remote file:
- 22.3 kB
- SHA256:
- 7fbb6f305da1600343d0c19abf3c25a78ecb01b89293c4a4be378c9bcae823fb
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