Instructions to use Pragformer/PragFormer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pragformer/PragFormer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Pragformer/PragFormer", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Pragformer/PragFormer", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Pragformer/PragFormer: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
-
https://huggingface.co/Pragformer/PragFormer/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
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hf download hf://Pragformer/PragFormer@refs/pr/1/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Pragformer/PragFormer/resolve/refs%2Fpr%2F1/tokenizer.json
2.11 MB
File too large to display, you can check the raw version instead.