Text Classification
Transformers
PyTorch
TensorBoard
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use responsibility-framing/predict-perception-xlmr-blame-victim with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use responsibility-framing/predict-perception-xlmr-blame-victim with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="responsibility-framing/predict-perception-xlmr-blame-victim")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("responsibility-framing/predict-perception-xlmr-blame-victim") model = AutoModelForSequenceClassification.from_pretrained("responsibility-framing/predict-perception-xlmr-blame-victim", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from responsibility-framing/predict-perception-xlmr-blame-victim: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/responsibility-framing/predict-perception-xlmr-blame-victim/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://responsibility-framing/predict-perception-xlmr-blame-victim/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/responsibility-framing/predict-perception-xlmr-blame-victim/resolve/main/pytorch_model.bin
1.11 GB
- Xet hash:
- 1642dc529e128ae1afbc7c346e716e2f5489d90bf7b846232be6a7aeaf1737a5
- Size of remote file:
- 1.11 GB
- SHA256:
- 952e55232e07f65dbf99d765cb4d513b427b437c4874b780635db9593b397b41
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.