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tesla_news_title_sentiment_analysis
YC9Z/tesla_news_title_sentiment_analysis
tesla_news_title_sentiment_analysis is a text classification model from YC9Z. Use it when you need a label for a piece of text. It is set up for transformers.
tunedbertmodel = BertForSequenceClassification.frompretrained('YC9Z/teslanewstitlesentimentanalysis', id2label={0: 'Neutral', 1: 'Positive', 2: 'Negative'})
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Apr 22, 2024
- Updated
- Apr 25, 2024
- SHA
- e53ea5ef
Try a prompt
Model card
From the Hugging Face model README
load model
tuned_bert_model = BertForSequenceClassification.from_pretrained('YC9Z/tesla_news_title_sentiment_analysis', id2label={0: 'Neutral', 1: 'Positive', 2: 'Negative'})
senti_tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
example:
inputs = senti_tokenizer("I like you. I love you", padding=True, truncation=True, max_length=512, return_tensors='pt')
outputs = tuned_bert_model(**inputs)
predictions = torch.nn.functional.softmax(outputs.logits, dim=-1)
predictions
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Apr 22, 2024
- Updated
- Apr 25, 2024