Instructions to use Kalindu/SinBerto with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kalindu/SinBerto with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Kalindu/SinBerto")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Kalindu/SinBerto") model = AutoModelForMaskedLM.from_pretrained("Kalindu/SinBerto", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
language: si
tags:
- SinBERTo
- Sinhala
- roberta
Overview
SinBerto is a small language model trained on a small news corpus. SinBerto is trained on Sinhala Language which is a low resource language compared to other languages.
Model Specifications.
model : Roberta
vocab_size=52_000, max_position_embeddings=514, num_attention_heads=12, num_hidden_layers=6, type_vocab_size=1
How to use from the Transformers Library
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("Kalindu/SinBerto")
model = AutoModelForMaskedLM.from_pretrained("Kalindu/SinBerto")
OR Clone the model repo
git lfs install
git clone https://huggingface.co/Kalindu/SinBerto