| | --- |
| | inference: false |
| | language: |
| | - bg |
| | license: mit |
| | datasets: |
| | - oscar |
| | - chitanka |
| | - wikipedia |
| | tags: |
| | - torch |
| | --- |
| | |
| | # ROBERTA BASE (cased) trained on private Bulgarian sentiment-analysis dataset |
| | This is a Multilingual Roberta model. |
| |
|
| | This model is cased: it does make a difference between bulgarian and Bulgarian. |
| |
|
| | ### How to use |
| |
|
| | Here is how to use this model in PyTorch: |
| |
|
| | ```python |
| | >>> import torch |
| | >>> from transformers import AutoModel, AutoTokenizer |
| | >>> |
| | >>> model_id = "rmihaylov/roberta-base-sentiment-bg" |
| | >>> model = AutoModel.from_pretrained(model_id, trust_remote_code=True) |
| | >>> tokenizer = AutoTokenizer.from_pretrained(model_id) |
| | >>> |
| | >>> inputs = tokenizer.batch_encode_plus(['Това е умно.', 'Това е тъпо.'], return_tensors='pt') |
| | >>> outputs = model(**inputs) |
| | >>> torch.softmax(outputs, dim=1).tolist() |
| | |
| | [[0.0004746630438603461, 0.9995253086090088], |
| | [0.9986956715583801, 0.0013043134240433574]] |
| | ``` |
| |
|
