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
- Xet hash:
- 5338836fce0731cfff4a558b2ed2b00a6bb79ce8332c49985bb1a90b1537ff1d
- Size of remote file:
- 469 MB
- SHA256:
- 4ae72d4e47a3808ad08557de284597a72b965f4ff9d6d31cbbaea10800747cf6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.