Instructions to use henryscheible/stereoset_binary_bert_classifieronly_0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use henryscheible/stereoset_binary_bert_classifieronly_0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="henryscheible/stereoset_binary_bert_classifieronly_0")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("henryscheible/stereoset_binary_bert_classifieronly_0") model = AutoModelForSequenceClassification.from_pretrained("henryscheible/stereoset_binary_bert_classifieronly_0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from henryscheible/stereoset_binary_bert_classifieronly_0: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/henryscheible/stereoset_binary_bert_classifieronly_0/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://henryscheible/stereoset_binary_bert_classifieronly_0/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/henryscheible/stereoset_binary_bert_classifieronly_0/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- bc46417d30e467f2d136cc7def1c0f9e81e904c286a9ff193f1656236aa0cc04
- Size of remote file:
- 438 MB
- SHA256:
- ff977ffc26d78ff4779da515ddb02b5a1c8143fad142d9a6a1f37a260919dfc6
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