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:
- b0b9e7c24983c336b53342550cb140fb9998b8bf1deb5944dc0258a549f9ec6c
- Size of remote file:
- 3.31 kB
- SHA256:
- c2e9e3d12424c5306cee00b40fb3201be73f8c26db28584659086039b1f685f2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.