Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Trained with AutoTrain
text-embeddings-inference
Instructions to use Hrishith123/Telugu-Distilbert-base-Multilingual-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hrishith123/Telugu-Distilbert-base-Multilingual-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Hrishith123/Telugu-Distilbert-base-Multilingual-uncased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Hrishith123/Telugu-Distilbert-base-Multilingual-uncased") model = AutoModelForSequenceClassification.from_pretrained("Hrishith123/Telugu-Distilbert-base-Multilingual-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Hrishith123/Telugu-Distilbert-base-Multilingual-uncased: direct link, hf CLI and curl.
- Browser
- Download file 2.92 MB
-
https://huggingface.co/Hrishith123/Telugu-Distilbert-base-Multilingual-uncased/resolve/main/tokenizer.json
- Command line
-
hf download hf://Hrishith123/Telugu-Distilbert-base-Multilingual-uncased/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Hrishith123/Telugu-Distilbert-base-Multilingual-uncased/resolve/main/tokenizer.json
2.92 MB
File too large to display, you can check the raw version instead.