Instructions to use alayaran/bodo-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alayaran/bodo-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="alayaran/bodo-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("alayaran/bodo-roberta-base") model = AutoModelForMaskedLM.from_pretrained("alayaran/bodo-roberta-base") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("alayaran/bodo-roberta-base")
model = AutoModelForMaskedLM.from_pretrained("alayaran/bodo-roberta-base")Quick Links
This is a roberta based configuration model for Bodo. It does not contain checkpoints for pretrained model. Its has only two things
- Byte Level BPE Tokenizer for Bodo
- Roberta base configuration
Uses
You can use tokenizer as following
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained('alayaran/bodo-roberta-base')
t = tokenizer('कौटि नख'राव दैनि कानेक्सन होबाय')
# {'input_ids': [310, 294, 313, 267, 503, 11, 268, 263, 277, 298, 287, 265, 267, 321, 263, 265, 272, 310, 273, 378, 295, 266, 271, 263, 269], 'attention_mask': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]}
# to decode
tokenizer.decode(t['input_ids'],skip_special_tokens=True)
# "कौटि नख'राव दैनि कानेक्सन होबाय"
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="alayaran/bodo-roberta-base")