Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use PracticalWork/xlm-roberta-large-classifier-prompted with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PracticalWork/xlm-roberta-large-classifier-prompted with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PracticalWork/xlm-roberta-large-classifier-prompted")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PracticalWork/xlm-roberta-large-classifier-prompted") model = AutoModelForSequenceClassification.from_pretrained("PracticalWork/xlm-roberta-large-classifier-prompted", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from PracticalWork/xlm-roberta-large-classifier-prompted: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/PracticalWork/xlm-roberta-large-classifier-prompted/resolve/main/tokenizer.json
- Command line
-
hf download hf://PracticalWork/xlm-roberta-large-classifier-prompted/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/PracticalWork/xlm-roberta-large-classifier-prompted/resolve/main/tokenizer.json
17.1 MB
- Size of remote file:
- 17.1 MB
- SHA256:
- 8373f9cd3d27591e1924426bcc1c8799bc5a9affc4fc857982c5d66668dd1f41
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