a mini zero-shot text classification implementation using streamlit and transformers
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Updated
Jan 19, 2022 - Python
a mini zero-shot text classification implementation using streamlit and transformers
An approach to extracting and summarizing key infrastructure and community impact information from wind disaster reconnaissance reports using Zero-shot text classification with BART-large models, highlighted by keywords.
The goal here is to develop a simple mock web app book library for demonstrating a possible use of AI for aiding users
Transformers, including the T5 and MarianMT, enabled effective understanding and generating complex programming codes. Consequently, they can help us in Data Security field. Let's see how!
LLMs for Low Resource Languages in Multilingual, Multimodal and Dialectal Settings
Comparing zero-shot and fine-tuned text classification transformer models across different review datasets
The source code used for paper "PIEClass: Weakly-Supervised Text Classification with Prompting and Noise-Robust Iterative Ensemble Training", published in EMNLP 2023.
Generalized Zero-Shot Character Recognition
Trying out with HuggingFace Models
Repository with the source code of our experiments for a multi-objective prioritization approach to optimize the execution of natural language test cases of a game.
Named Entity Recognition to detect landmarks in German texts
Applying zero-shot learning on classification task.
Code for EMNLP2019 paper : "Benchmarking zero-shot text classification: datasets, evaluation and entailment approach"
[ICML 2024] "Visual-Text Cross Alignment: Refining the Similarity Score in Vision-Language Models"
For NYC GAI/LLM Hackathon.
Detect Emotions on Christmas Lyrics with Zero-shot Emotion Classification. With the help of Streamlit and Plotly.
Zero-shot matching of professional training titles with their corresponding positions/labor market field
Exploring fast & accurate zero-shot text classification
Various NLP tasks for Global Health Analysis, including an automatic Named Entity Recognition (NER) pipeline to annotate Global Digital Health Documents.
Low-latency ONNX and TensorRT image segmentation with contrastive language-image pre-training based prompts
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