Instructions to use PursuitOfDataScience/finetuned_sentiment_bert_base_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PursuitOfDataScience/finetuned_sentiment_bert_base_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PursuitOfDataScience/finetuned_sentiment_bert_base_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PursuitOfDataScience/finetuned_sentiment_bert_base_model") model = AutoModelForSequenceClassification.from_pretrained("PursuitOfDataScience/finetuned_sentiment_bert_base_model") - Notebooks
- Google Colab
- Kaggle
Y. Yu commited on
Create README.md
Browse files
README.md
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---
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datasets:
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- stanfordnlp/imdb
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language:
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- en
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metrics:
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- accuracy: 0.9418
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- recall: 0.9418
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- f1: 0.9417991595798644
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- precision: 0.9418255198420261
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pipeline_tag: text-classification
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