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:
- 856838c62bd4a9e3359b60d17c28f704625f524353e3358bf3028e72e49d2741
- Size of remote file:
- 1.11 GB
- SHA256:
- bab9e6f3cbaa64b6adc5582d06279ae27d8418941ca378ebe75c985da8882d4c
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