Instructions to use henryscheible/xlnet-base-cased_winobias_finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use henryscheible/xlnet-base-cased_winobias_finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="henryscheible/xlnet-base-cased_winobias_finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("henryscheible/xlnet-base-cased_winobias_finetuned") model = AutoModelForSequenceClassification.from_pretrained("henryscheible/xlnet-base-cased_winobias_finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from henryscheible/xlnet-base-cased_winobias_finetuned: direct link, hf CLI and curl.
- Browser
- Download file 469 MB
-
https://huggingface.co/henryscheible/xlnet-base-cased_winobias_finetuned/resolve/d80b79ee154d46a5f2f1d3ec6f97d5c05439b061/pytorch_model.bin
- Command line
-
hf download hf://henryscheible/xlnet-base-cased_winobias_finetuned@d80b79ee154d46a5f2f1d3ec6f97d5c05439b061/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/henryscheible/xlnet-base-cased_winobias_finetuned/resolve/d80b79ee154d46a5f2f1d3ec6f97d5c05439b061/pytorch_model.bin
469 MB
- Xet hash:
- 376950aae07e27f54787edf41e4994d06c9be4503c284672efd005a82725b134
- Size of remote file:
- 469 MB
- SHA256:
- b6811110c99ebf3cbcda2647d180c1588ff4e6f2de0d289a24c38a87e2c27187
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