Instructions to use henryscheible/stereoset_binary_bert_classifieronly with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use henryscheible/stereoset_binary_bert_classifieronly with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="henryscheible/stereoset_binary_bert_classifieronly")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("henryscheible/stereoset_binary_bert_classifieronly") model = AutoModelForSequenceClassification.from_pretrained("henryscheible/stereoset_binary_bert_classifieronly", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from henryscheible/stereoset_binary_bert_classifieronly: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/henryscheible/stereoset_binary_bert_classifieronly/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://henryscheible/stereoset_binary_bert_classifieronly@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/henryscheible/stereoset_binary_bert_classifieronly/resolve/refs%2Fpr%2F1/pytorch_model.bin
438 MB
- Xet hash:
- 4d5e306e0ac426d4f7ed59fce2e8460d7cdaa823e2cc55a0acc1c4ad2447bd96
- Size of remote file:
- 438 MB
- SHA256:
- b4ad298bc1191352d90b370463e214f5efb7b3040e8e38ae90b7764955670f2b
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