Instructions to use philipobiorah/bert-imdb-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philipobiorah/bert-imdb-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="philipobiorah/bert-imdb-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("philipobiorah/bert-imdb-model") model = AutoModelForSequenceClassification.from_pretrained("philipobiorah/bert-imdb-model") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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- **Labels**:
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- `0`: Negative
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- `1`: Positive
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| **Model** | **SST-2 Accuracy** | **Yelp Accuracy** | **Amazon Accuracy** | **IMDB Accuracy** |
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| **philipobiorah/bert-imdb-model** | **0.89** | **0.89** | **0.89** | **0.96** |
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| **RoBERTa-Sentiment** | **0.40** | **0.42** | **0.47** | **0.79** |
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| **Logistic Regression** | **0.83** | **0.91** | **0.86** | **0.85** |
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| **Naive Bayes** | **0.77** | **0.86** | **0.84** | **0.85** |
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## Usage
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### **Load the Model in Python**
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```python
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- **Labels**:
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- `0`: Negative
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- `1`: Positive
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## Evaluation
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| **Model** | **SST-2 Accuracy** | **Yelp Accuracy** | **Amazon Accuracy** | **IMDB Accuracy** |
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| **philipobiorah/bert-imdb-model** | **0.89** | **0.89** | **0.89** | **0.96** |
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| **RoBERTa-Sentiment** | **0.40** | **0.42** | **0.47** | **0.79** |
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| **Logistic Regression** | **0.83** | **0.91** | **0.86** | **0.85** |
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| **Naive Bayes** | **0.77** | **0.86** | **0.84** | **0.85** |
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## Usage
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### **Load the Model in Python**
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```python
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