Text Classification
Transformers
PyTorch
TensorBoard
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use responsibility-framing/predict-perception-xlmr-focus-object with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use responsibility-framing/predict-perception-xlmr-focus-object with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="responsibility-framing/predict-perception-xlmr-focus-object")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("responsibility-framing/predict-perception-xlmr-focus-object") model = AutoModelForSequenceClassification.from_pretrained("responsibility-framing/predict-perception-xlmr-focus-object", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download .gitignore from responsibility-framing/predict-perception-xlmr-focus-object: direct link, hf CLI and curl.
- Browser
- Download file 13 Bytes
-
https://huggingface.co/responsibility-framing/predict-perception-xlmr-focus-object/resolve/main/.gitignore
- Command line
-
hf download hf://responsibility-framing/predict-perception-xlmr-focus-object/.gitignore
-
curl -L -o .gitignore https://huggingface.co/responsibility-framing/predict-perception-xlmr-focus-object/resolve/main/.gitignore
13 Bytes
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