# Deberta for Sentiment Analysis

This is a Deberta model finetuned on over 1 million reviews from Amazon's multi-reviews dataset.


## How to use the model

```python
import torch
from transformers import AutoModelForSequenceClassification, AutoTokenizer

def get_sentiment(sentence):
    bert_dict = {}
    vectors = tokenizer(sentence, return_tensors='pt').to(device)
    outputs = bert_model(**vectors).logits
    probs = torch.nn.functional.softmax(outputs, dim = 1)[0]
    bert_dict['neg'] = round(probs[0].item(), 3)
    bert_dict['neu'] = round(probs[1].item(), 3)
    bert_dict['pos'] = round(probs[2].item(), 3)
    return bert_dict

MODEL_NAME = 'RashidNLP/Amazon-Deberta-Base-Sentiment'
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')

bert_model = AutoModelForSequenceClassification.from_pretrained(MODEL_NAME, num_labels = 3).to(device)
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)

get_sentiment("This is quite a mess you have made")

```
{"language": ["en"], "license": "mit", "library_name": "transformers", "tags": ["Text Classification", "Pytorch", "Sentiment_Analysis", "Deberta"], "datasets": ["amazon_reviews_multi"]}
transformers pytorch safetensors deberta-v2 text-classification Text Classification Pytorch Sentiment_Analysis Deberta en dataset:amazon_reviews_multi license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #deberta-v2 #text-classification #Text Classification #Pytorch #Sentiment_Analysis #Deberta #en #dataset-amazon_reviews_multi #license-mit #autotrain_compatible #endpoints_compatible #region-us 

# Deberta for Sentiment Analysis

This is a Deberta model finetuned on over 1 million reviews from Amazon's multi-reviews dataset.


## How to use the model


# Deberta for Sentiment Analysis

This is a Deberta model finetuned on over 1 million reviews from Amazon's multi-reviews dataset. ## How to use the model
TAGS
#transformers #pytorch #safetensors #deberta-v2 #text-classification #Text Classification #Pytorch #Sentiment_Analysis #Deberta #en #dataset-amazon_reviews_multi #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 # Deberta for Sentiment Analysis

This is a Deberta model finetuned on over 1 million reviews from Amazon's multi-reviews dataset. ## How to use the model