Text Classification
Transformers
PyTorch
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use IIIT-L/muril-base-cased-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/muril-base-cased-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/muril-base-cased-finetuned-code-mixed-DS")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIIT-L/muril-base-cased-finetuned-code-mixed-DS") model = AutoModelForSequenceClassification.from_pretrained("IIIT-L/muril-base-cased-finetuned-code-mixed-DS") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f9c3547d1b66a2e3f6296481f196c9a34c792e30965cb6daf9851225365f4b6a
- Size of remote file:
- 950 MB
- SHA256:
- ffc7667364ce35f08c7cab416023ed75543aaf50ed58217896555f733cbb2f42
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.