Instructions to use clarin-pl/FastPDN-distiluse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use clarin-pl/FastPDN-distiluse with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="clarin-pl/FastPDN-distiluse")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("clarin-pl/FastPDN-distiluse") model = AutoModelForTokenClassification.from_pretrained("clarin-pl/FastPDN-distiluse", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from clarin-pl/FastPDN-distiluse: direct link, hf CLI and curl.
- Browser
- Download file 539 MB
-
https://huggingface.co/clarin-pl/FastPDN-distiluse/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://clarin-pl/FastPDN-distiluse@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/clarin-pl/FastPDN-distiluse/resolve/refs%2Fpr%2F1/pytorch_model.bin
539 MB
- Xet hash:
- bd101c123e0e617399b221eb49868018b1ab01c2a91a271005025075a3a8676b
- Size of remote file:
- 539 MB
- SHA256:
- 73f8a374e3182af71f81d43d7e9b36e0bacef11195b7b01cbcab4a0c12364e29
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