Instructions to use henryscheible/stereoset_binary_roberta-base_classifieronly with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use henryscheible/stereoset_binary_roberta-base_classifieronly with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="henryscheible/stereoset_binary_roberta-base_classifieronly")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("henryscheible/stereoset_binary_roberta-base_classifieronly") model = AutoModelForSequenceClassification.from_pretrained("henryscheible/stereoset_binary_roberta-base_classifieronly", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from henryscheible/stereoset_binary_roberta-base_classifieronly: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/henryscheible/stereoset_binary_roberta-base_classifieronly/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://henryscheible/stereoset_binary_roberta-base_classifieronly/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/henryscheible/stereoset_binary_roberta-base_classifieronly/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 6f9af20ab03ccc52c8e34d3df0e4ed35f82325fad65ad4f8bf82bf242cc65e35
- Size of remote file:
- 499 MB
- SHA256:
- da093caf02931ca09d61f47e30528d79095cd31bdcdbef1985c9e46140d906f8
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