Text Classification
Transformers
PyTorch
Bengali
albert
collaborative
bengali
SequenceClassification
Instructions to use neuropark/sahajBERT-NCC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use neuropark/sahajBERT-NCC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="neuropark/sahajBERT-NCC")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("neuropark/sahajBERT-NCC") model = AutoModelForSequenceClassification.from_pretrained("neuropark/sahajBERT-NCC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from neuropark/sahajBERT-NCC: direct link, hf CLI and curl.
- Browser
- Download file 1.72 MB
-
https://huggingface.co/neuropark/sahajBERT-NCC/resolve/main/tokenizer.json
- Command line
-
hf download hf://neuropark/sahajBERT-NCC/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/neuropark/sahajBERT-NCC/resolve/main/tokenizer.json
1.72 MB
File too large to display, you can check the raw version instead.