
# Keras model with ruBERT conversational embedder for Sentiment Analysis
Russian texts sentiment classification.

Model trained on [Tatyana/ru_sentiment_dataset](https://huggingface.co/datasets/Tatyana/ru_sentiment_dataset)

## Labels meaning
    0: NEUTRAL
    1: POSITIVE
    2: NEGATIVE

## How to use
```python

!pip install tensorflow-gpu
!pip install deeppavlov
!python -m deeppavlov install squad_bert
!pip install fasttext
!pip install transformers
!python -m deeppavlov install bert_sentence_embedder

from deeppavlov import build_model

model = build_model(Tatyana/rubert_conversational_cased_sentiment/custom_config.json)
model(["Сегодня хорошая погода", "Я счастлив проводить с тобою время", "Мне нравится эта музыкальная композиция"])

```



{"language": ["ru"], "tags": ["sentiment", "text-classification"], "datasets": ["Tatyana/ru_sentiment_dataset"]}
transformers pytorch bert sentiment text-classification ru dataset:Tatyana/ru_sentiment_dataset endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #sentiment #text-classification #ru #dataset-Tatyana/ru_sentiment_dataset #endpoints_compatible #region-us 


# Keras model with ruBERT conversational embedder for Sentiment Analysis
Russian texts sentiment classification.

Model trained on Tatyana/ru_sentiment_dataset

## Labels meaning
    0: NEUTRAL
    1: POSITIVE
    2: NEGATIVE

## How to use




# Keras model with ruBERT conversational embedder for Sentiment Analysis
Russian texts sentiment classification.

Model trained on Tatyana/ru_sentiment_dataset ## Labels meaning
    0: NEUTRAL
    1: POSITIVE
    2: NEGATIVE ## How to use
TAGS
#transformers #pytorch #bert #sentiment #text-classification #ru #dataset-Tatyana/ru_sentiment_dataset #endpoints_compatible #region-us 
 # Keras model with ruBERT conversational embedder for Sentiment Analysis
Russian texts sentiment classification.

Model trained on Tatyana/ru_sentiment_dataset ## Labels meaning
    0: NEUTRAL
    1: POSITIVE
    2: NEGATIVE ## How to use
passage: TAGS
#transformers #pytorch #bert #sentiment #text-classification #ru #dataset-Tatyana/ru_sentiment_dataset #endpoints_compatible #region-us 
# Keras model with ruBERT conversational embedder for Sentiment Analysis
Russian texts sentiment classification.

Model trained on Tatyana/ru_sentiment_dataset## Labels meaning
    0: NEUTRAL
    1: POSITIVE
    2: NEGATIVE## How to use