Text Classification
Transformers
PyTorch
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use IIIT-L/xlm-roberta-large-finetuned-TRAC-DS-new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIIT-L/xlm-roberta-large-finetuned-TRAC-DS-new with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="IIIT-L/xlm-roberta-large-finetuned-TRAC-DS-new")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIIT-L/xlm-roberta-large-finetuned-TRAC-DS-new") model = AutoModelForSequenceClassification.from_pretrained("IIIT-L/xlm-roberta-large-finetuned-TRAC-DS-new") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f55496596534aeea74cbd7fed962a15f117a73f92864a8b0a389a82e9b767f59
- Size of remote file:
- 2.24 GB
- SHA256:
- 65a6c1428fea0d7bbcb370891df71d437eddd2b8b79a40da954994f7decf80fa
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