# Description:

This is a smaller per-trained model on Tamil Language using Masked Language Modeling(MLM). And the model is trained on Oscar Tamil dataset.

# How to Use:
The model can be used directly with a pipeline for masked language modeling:
```python
>>> from transformers import AutoTokenizer, AutoModelForMaskedLM, pipeline
>>> tokenizer = AutoTokenizer.from_pretrained("d42kw01f/Tamil-RoBERTa")
>>> model = AutoModelForMaskedLM.from_pretrained("d42kw01f/Tamil-RoBERTa")
>>> fill_mask = pipeline('fill-mask', model=model, tokenizer=tokenizer)
>>> fill_mask("நான் வீட்டு <mask>.")
```
{}
transformers pytorch roberta fill-mask autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #fill-mask #autotrain_compatible #endpoints_compatible #region-us 

# Description:

This is a smaller per-trained model on Tamil Language using Masked Language Modeling(MLM). And the model is trained on Oscar Tamil dataset.

# How to Use:
The model can be used directly with a pipeline for masked language modeling:

# Description:

This is a smaller per-trained model on Tamil Language using Masked Language Modeling(MLM). And the model is trained on Oscar Tamil dataset. # How to Use:
The model can be used directly with a pipeline for masked language modeling:
TAGS
#transformers #pytorch #roberta #fill-mask #autotrain_compatible #endpoints_compatible #region-us 
 # Description:

This is a smaller per-trained model on Tamil Language using Masked Language Modeling(MLM). And the model is trained on Oscar Tamil dataset. # How to Use:
The model can be used directly with a pipeline for masked language modeling:
passage: TAGS
#transformers #pytorch #roberta #fill-mask #autotrain_compatible #endpoints_compatible #region-us 
# Description:

This is a smaller per-trained model on Tamil Language using Masked Language Modeling(MLM). And the model is trained on Oscar Tamil dataset.# How to Use:
The model can be used directly with a pipeline for masked language modeling: