
# 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:
```python
from transformers import pipeline
unmasker = pipeline('fill-mask', model='ksnugroho/feelin-base-uncased')
unmasker("Adik sedang <mask> sepak bola <mask> lapangan")
```

Load tokenizer:
```python
from transformers import RobertaTokenizer
tokenizer = RobertaTokenizer.from_pretrained('ksnugroho/feelin-base-uncased')
```

Load model in PyTorch:
```python
from transformers import RobertaModel
model = RobertaModel.from_pretrained('ksnugroho/feelin-base-uncased')
```

and in TensorFlow:
```python
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
{"language": ["id"], "license": "mit", "pipeline_tag": "fill-mask", "widget": [{"text": "Adik sedang <mask> sepak bola di lapangan."}]}
transformers pytorch roberta fill-mask id license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #fill-mask #id #license-mit #autotrain_compatible #endpoints_compatible #region-us 


# 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:


Load tokenizer:


Load model in PyTorch:


and in TensorFlow:

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
# 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:


Load tokenizer:


Load model in PyTorch:


and in TensorFlow:

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
TAGS
#transformers #pytorch #roberta #fill-mask #id #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 # 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:


Load tokenizer:


Load model in PyTorch:


and in TensorFlow:

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
TAGS
#transformers #pytorch #roberta #fill-mask #id #license-mit #autotrain_compatible #endpoints_compatible #region-us 
# 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:


Load tokenizer:


Load model in PyTorch:


and in TensorFlow:

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