Fill-Mask
Transformers
Safetensors
Telugu
bert
pretraining
bert-tiny
telugu
masked-language-modeling
next-sentence-prediction
google-recipe
Eval Results (legacy)
Instructions to use bammera-pothana/BERT-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bammera-pothana/BERT-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="bammera-pothana/BERT-tiny")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("bammera-pothana/BERT-tiny") model = AutoModelForPreTraining.from_pretrained("bammera-pothana/BERT-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from bammera-pothana/BERT-tiny: direct link, hf CLI and curl.
- Browser
- Download file 1.08 MB
-
https://huggingface.co/bammera-pothana/BERT-tiny/resolve/main/tokenizer.json
- Command line
-
hf download hf://bammera-pothana/BERT-tiny/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/bammera-pothana/BERT-tiny/resolve/main/tokenizer.json
1.08 MB
File too large to display, you can check the raw version instead.