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 pytorch_model.bin from responsibility-framing/predict-perception-bert-blame-none: direct link, hf CLI and curl.
- Browser
- Download file 443 MB
-
https://huggingface.co/responsibility-framing/predict-perception-bert-blame-none/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://responsibility-framing/predict-perception-bert-blame-none/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/responsibility-framing/predict-perception-bert-blame-none/resolve/main/pytorch_model.bin
443 MB
- Xet hash:
- 5b8b2a59b403db0e00fa0a9ca50b7c412b4d905a5b02a204a0beb8f8a40708f3
- Size of remote file:
- 443 MB
- SHA256:
- 61f332ebe22b2318ad305bf7c3fb8a0092a14c38c6c734e2eead05c204283414
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