Instructions to use fxmarty/tiny-random-longformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fxmarty/tiny-random-longformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="fxmarty/tiny-random-longformer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("fxmarty/tiny-random-longformer") model = AutoModel.from_pretrained("fxmarty/tiny-random-longformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from fxmarty/tiny-random-longformer: direct link, hf CLI and curl.
- Browser
- Download file 3.52 MB
-
https://huggingface.co/fxmarty/tiny-random-longformer/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://fxmarty/tiny-random-longformer@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/fxmarty/tiny-random-longformer/resolve/refs%2Fpr%2F1/pytorch_model.bin
3.52 MB
- Xet hash:
- c73fab58c577a75ed1b3a6f2fff8dcf15d2eb3e5530f3164ae48637c844de464
- Size of remote file:
- 3.52 MB
- SHA256:
- 4359117fdf9e0f477de96cac2cb26e9e4fb392a49b43210fa04d4776df1a5605
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