Instructions to use henryscheible/stereoset_binary_roberta-large_classifieronly with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use henryscheible/stereoset_binary_roberta-large_classifieronly with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="henryscheible/stereoset_binary_roberta-large_classifieronly")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("henryscheible/stereoset_binary_roberta-large_classifieronly") model = AutoModelForSequenceClassification.from_pretrained("henryscheible/stereoset_binary_roberta-large_classifieronly", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from henryscheible/stereoset_binary_roberta-large_classifieronly: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/henryscheible/stereoset_binary_roberta-large_classifieronly/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://henryscheible/stereoset_binary_roberta-large_classifieronly/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/henryscheible/stereoset_binary_roberta-large_classifieronly/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- 882d6c277c63594ef54acdcb27d6970a4b3fd5ae3cd3cc91e9b6ae1ba33fa719
- Size of remote file:
- 1.42 GB
- SHA256:
- 6b279f6c72f060aa8c9ecc8590ddfb693efaec645e6e0b0129b89954fe79a2e5
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