Instructions to use callmesan/indic-bert-roman-urdu-fine-grained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use callmesan/indic-bert-roman-urdu-fine-grained with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="callmesan/indic-bert-roman-urdu-fine-grained")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("callmesan/indic-bert-roman-urdu-fine-grained") model = AutoModelForSequenceClassification.from_pretrained("callmesan/indic-bert-roman-urdu-fine-grained", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b9563bc038b1de11f0dfe4262dd205ab74c41d54e3a38f1b8185a2660181c027
- Size of remote file:
- 134 MB
- SHA256:
- 426c7a0e2de91b207986009e4c23def221e33e17c5007a59487ee0201dbcce55
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.