bert-sklearn
ABSA_Project_4
| bert-sklearn | ABSA_Project_4 | |
|---|---|---|
| 1 | 1 | |
| 293 | 0 | |
| - | - | |
| 0.0 | 0.0 | |
| over 1 year ago | almost 2 years ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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bert-sklearn
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Quick BERT Pre-Trained Model for Sentiment Analysis with Scikit Wrapper
Sckit-learn wrapper provided by Charles Nainan. GitHub of Scikit Learn BERT wrapper.
ABSA_Project_4
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Quick BERT Pre-Trained Model for Sentiment Analysis with Scikit Wrapper
github: https://github.com/ddey117/Product_Twitter_Sentiment_Classification
What are some alternatives?
bert - TensorFlow code and pre-trained models for BERT
OpenAI-CLIP - Simple implementation of OpenAI CLIP model in PyTorch.
kruk - Ukrainian instruction-tuned language models and datasets
NLU-engine-prototype-benchmarks - Demo and benchmarks for building an NLU engine similar to those in voice assistants. Several intent classifiers are implemented and benchmarked. Conditional Random Fields (CRFs) are used for entity extraction.
fake-news - Building a fake news detector from initial ideation to model deployment
tf-transformers - State of the art faster Transformer with Tensorflow 2.0 ( NLP, Computer Vision, Audio ).
TabularSemanticParsing - Translating natural language questions to a structured query language
German-NER-BERT - German NER on Legal Data using BERT
pytorch-sentiment-analysis - Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
adaptnlp - An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.
haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.