Fill-Mask
Transformers
Safetensors
Khasi
roberta
khasi
bert
masked-lm
foundational-model
low-resource
indian-language
meghalaya
austroasiatic
Instructions to use MWirelabs/khasibert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MWirelabs/khasibert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="MWirelabs/khasibert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("MWirelabs/khasibert") model = AutoModelForMaskedLM.from_pretrained("MWirelabs/khasibert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from MWirelabs/khasibert: direct link, hf CLI and curl.
- Browser
- Download file 2.23 MB
-
https://huggingface.co/MWirelabs/khasibert/resolve/main/tokenizer.json
- Command line
-
hf download hf://MWirelabs/khasibert/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/MWirelabs/khasibert/resolve/main/tokenizer.json
2.23 MB
File too large to display, you can check the raw version instead.