
## RoBERTa Latin base model Version 2 (Uncased)

### Prerequisites

transformers==4.19.2

### Model architecture

This model uses RoBERTa base setttings except vocabulary size.

### Tokenizer

Using BPE tokenizer with a vocabulary size 50,000.

### Training Data 

* Subset of [CC-100/la](https://data.statmt.org/cc-100/) : Monolingual Datasets from Web Crawl Data

### Usage

```python
from transformers import pipeline

unmasker = pipeline('fill-mask', model='ClassCat/roberta-base-latin-v2')
unmasker("vita brevis, ars <mask>")
```
{"language": "la", "license": "cc-by-sa-4.0", "datasets": ["cc100"], "widget": [{"text": "quod est tibi <mask> ?\""}, {"text": "vita brevis, ars <mask>."}, {"text": "errare <mask> est."}, {"text": "usus est magister <mask>."}]}
transformers pytorch roberta fill-mask la dataset:cc100 license:cc-by-sa-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #fill-mask #la #dataset-cc100 #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 


## RoBERTa Latin base model Version 2 (Uncased)

### Prerequisites

transformers==4.19.2

### Model architecture

This model uses RoBERTa base setttings except vocabulary size.

### Tokenizer

Using BPE tokenizer with a vocabulary size 50,000.

### Training Data 

* Subset of CC-100/la : Monolingual Datasets from Web Crawl Data

### Usage


## RoBERTa Latin base model Version 2 (Uncased) ### Prerequisites

transformers==4.19.2 ### Model architecture

This model uses RoBERTa base setttings except vocabulary size. ### Tokenizer

Using BPE tokenizer with a vocabulary size 50,000. ### Training Data 

* Subset of CC-100/la : Monolingual Datasets from Web Crawl Data ### Usage
TAGS
#transformers #pytorch #roberta #fill-mask #la #dataset-cc100 #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 
 ## RoBERTa Latin base model Version 2 (Uncased) ### Prerequisites

transformers==4.19.2 ### Model architecture

This model uses RoBERTa base setttings except vocabulary size. ### Tokenizer

Using BPE tokenizer with a vocabulary size 50,000. ### Training Data 

* Subset of CC-100/la : Monolingual Datasets from Web Crawl Data ### Usage
passage: TAGS
#transformers #pytorch #roberta #fill-mask #la #dataset-cc100 #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 
## RoBERTa Latin base model Version 2 (Uncased)### Prerequisites

transformers==4.19.2### Model architecture

This model uses RoBERTa base setttings except vocabulary size.### Tokenizer

Using BPE tokenizer with a vocabulary size 50,000.### Training Data 

* Subset of CC-100/la : Monolingual Datasets from Web Crawl Data### Usage