Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use responsibility-framing/predict-perception-bert-blame-none with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use responsibility-framing/predict-perception-bert-blame-none with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="responsibility-framing/predict-perception-bert-blame-none")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("responsibility-framing/predict-perception-bert-blame-none") model = AutoModelForSequenceClassification.from_pretrained("responsibility-framing/predict-perception-bert-blame-none", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from responsibility-framing/predict-perception-bert-blame-none: direct link, hf CLI and curl.
- Browser
- Download file 3.12 kB
-
https://huggingface.co/responsibility-framing/predict-perception-bert-blame-none/resolve/main/training_args.bin
- Command line
-
hf download hf://responsibility-framing/predict-perception-bert-blame-none/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/responsibility-framing/predict-perception-bert-blame-none/resolve/main/training_args.bin
3.12 kB
- Xet hash:
- bb43aa9d59f39cabf1ebacbd27634100836471555370ce64e534db6691d48d4d
- Size of remote file:
- 3.12 kB
- SHA256:
- 27e64f34c7133123ce098edd0d6c442fb7e110b99ed2aa0a8e4b31ecbab50376
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