Downloads · 30 days
14
5% of all-time downloads
feelin-base-uncased
ksnugroho/feelin-base-uncased
feelin-base-uncased is a fill-mask model from ksnugroho. Use it when you need the model to fill a missing word. It is set up for transformers. The card lists the license as mit.
FEEL-IN is a state-of-the-art language model for Indonesian based on the RoBERTa model. The pre-trained model is trained using a masked language modeling (MLM) objective.
All-time downloads
311
Public
Repo size
499 MB
Likes
1
Public
Repo makeup
Click a slice to open those files.
.bin499 MB · 100%
At a glance
- Task
- Fill-Mask
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Jan 12, 2023
- Updated
- Jan 12, 2023
- SHA
- 7712f309
Try a prompt
Model card
From the Hugging Face model README
Model Descripstion
FEEL-IN is a state-of-the-art language model for Indonesian based on the RoBERTa model. The pre-trained model is trained using a masked language modeling (MLM) objective.
How to Use
You can use this model directly with a pipeline for masked language modeling:
from transformers import pipeline
unmasker = pipeline('fill-mask', model='ksnugroho/feelin-base-uncased')
unmasker("Adik sedang <mask> sepak bola <mask> lapangan")
Load tokenizer:
from transformers import RobertaTokenizer
tokenizer = RobertaTokenizer.from_pretrained('ksnugroho/feelin-base-uncased')
Load model in PyTorch:
from transformers import RobertaModel
model = RobertaModel.from_pretrained('ksnugroho/feelin-base-uncased')
and in TensorFlow:
from transformers import TFRobertaModel
model = TFRobertaModel.from_pretrained('ksnugroho/feelin-base-uncased')
tested with transformers==4.25.1
Authors
FEEL-IN was trained and evaluated by Kuncahyo Setyo Nugroho, Fitra Abdurrachman Bachtiar, Wayan Firdaus Mahmudy<br> Intelligent Systems Lab, Faculty of Computer Science, Brawijaya University, Indonesia
- Task
- Fill-Mask
- Library
- transformers
- Type
- roberta
- License
- mit
- Languages
- id
- Created
- Jan 12, 2023
- Updated
- Jan 12, 2023