Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Areepatw/xlmroberta-multirc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Areepatw/xlmroberta-multirc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Areepatw/xlmroberta-multirc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Areepatw/xlmroberta-multirc") model = AutoModelForSequenceClassification.from_pretrained("Areepatw/xlmroberta-multirc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Areepatw/xlmroberta-multirc: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/Areepatw/xlmroberta-multirc/resolve/main/tokenizer.json
- Command line
-
hf download hf://Areepatw/xlmroberta-multirc/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Areepatw/xlmroberta-multirc/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 900d575674d5bfcd5c2b9059c9221a42f92c957ed7230f7e096d3e9580c3e4c2
- Size of remote file:
- 17.1 MB
- SHA256:
- 883b037111086fd4dfebbbc9b7cee11e1517b5e0c0514879478661440f137085
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