
# nepbert

## Model description

Roberta trained from scratch on the Nepali CC-100 dataset with 12 million sentences.

## Intended uses & limitations

#### How to use

```python
from transformers import pipeline

pipe = pipeline(
    "fill-mask",
    model="amitness/nepbert",
    tokenizer="amitness/nepbert"
)
print(pipe(u"तिमीलाई कस्तो <mask>?"))
```

## Training data

The data was taken from the nepali language subset of CC-100 dataset.

## Training procedure
The model was trained on Google Colab using `1x Tesla V100`.
{"language": ["ne"], "license": "mit", "tags": ["roberta", "nepali-laguage-model"], "datasets": ["cc100"], "widget": [{"text": "\u0924\u093f\u092e\u0940\u0932\u093e\u0908 \u0915\u0938\u094d\u0924\u094b <mask>?"}]}
transformers pytorch jax safetensors roberta fill-mask nepali-laguage-model ne dataset:cc100 license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #jax #safetensors #roberta #fill-mask #nepali-laguage-model #ne #dataset-cc100 #license-mit #autotrain_compatible #endpoints_compatible #region-us 


# nepbert

## Model description

Roberta trained from scratch on the Nepali CC-100 dataset with 12 million sentences.

## Intended uses & limitations

#### How to use



## Training data

The data was taken from the nepali language subset of CC-100 dataset.

## Training procedure
The model was trained on Google Colab using '1x Tesla V100'.
# nepbert ## Model description

Roberta trained from scratch on the Nepali CC-100 dataset with 12 million sentences. ## Intended uses & limitations #### How to use ## Training data

The data was taken from the nepali language subset of CC-100 dataset. ## Training procedure
The model was trained on Google Colab using '1x Tesla V100'.
TAGS
#transformers #pytorch #jax #safetensors #roberta #fill-mask #nepali-laguage-model #ne #dataset-cc100 #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 # nepbert ## Model description

Roberta trained from scratch on the Nepali CC-100 dataset with 12 million sentences. ## Intended uses & limitations #### How to use ## Training data

The data was taken from the nepali language subset of CC-100 dataset. ## Training procedure
The model was trained on Google Colab using '1x Tesla V100'.
passage: TAGS
#transformers #pytorch #jax #safetensors #roberta #fill-mask #nepali-laguage-model #ne #dataset-cc100 #license-mit #autotrain_compatible #endpoints_compatible #region-us 
# nepbert## Model description

Roberta trained from scratch on the Nepali CC-100 dataset with 12 million sentences.## Intended uses & limitations#### How to use## Training data

The data was taken from the nepali language subset of CC-100 dataset.## Training procedure
The model was trained on Google Colab using '1x Tesla V100'.