Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Abhi964/MahaPhrase_MBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Abhi964/MahaPhrase_MBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Abhi964/MahaPhrase_MBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Abhi964/MahaPhrase_MBERT") model = AutoModelForSequenceClassification.from_pretrained("Abhi964/MahaPhrase_MBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4cfe387eb80ce9c03ee777a5ab676b0c07b106ca4a6f908b8d31ac0823b9dfdb
- Size of remote file:
- 711 MB
- SHA256:
- 70c6e6943d719344a156653b7c89c37d2361254cd4226bbf127f63c9fba07489
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