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README.md

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----
-tags:
-  - text-classification
-  - pytorch
-  - transformers
-library_name: transformers
-language: en
-datasets:
-  - yelp_review
-model_type: bert
----
-# Sentiment Analysis Model: Fine-tuned BERT Base
-
-This model is a fine-tuned version of `bert-base-cased` on the Yelp Reviews dataset for sentiment analysis.
-
-## Intended Use
-
-This model predicts the sentiment of a given text, classifying it as either:
-- `positive`
-- `negative`
-
-## Example Usage
-
-```python
-from transformers import AutoTokenizer, AutoModelForSequenceClassification
-
-model_name = "your-username/your-model-name"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForSequenceClassification.from_pretrained(model_name)
-
-inputs = tokenizer("This restaurant is amazing!", return_tensors="pt")
-outputs = model(**inputs)
-logits = outputs.logits
-print(logits)