Text Classification
Transformers
PyTorch
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use IIIT-L/xlm-roberta-base-finetuned-code-mixed-DS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIIT-L/xlm-roberta-base-finetuned-code-mixed-DS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="IIIT-L/xlm-roberta-base-finetuned-code-mixed-DS")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIIT-L/xlm-roberta-base-finetuned-code-mixed-DS") model = AutoModelForSequenceClassification.from_pretrained("IIIT-L/xlm-roberta-base-finetuned-code-mixed-DS") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d083038f36b119764bc680199e6b5e24c16a760d7157a7c4170bd903ce64cf3
- Size of remote file:
- 3.31 kB
- SHA256:
- c62d154e88877e93e586a655ebf0f55b48b38a855746b051a233d5d838f7e383
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