Applying NLP transfer learning techniques to predict Tweet stance toward a topic
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Updated
Feb 10, 2019 - Jupyter Notebook
Applying NLP transfer learning techniques to predict Tweet stance toward a topic
The code to reproduce results from paper "MultiFiT: Efficient Multi-lingual Language Model Fine-tuning" https://arxiv.org/abs/1909.04761
中文ULMFiT 情感分析 文本分类
One-Stop Solution to encode sentence to fixed length vectors from various embedding techniques
Language Modeling and Text Classification in Malayalam Language using ULMFiT
Stack Overflow question tagging. Find the tutorial on Medium
sequence tagging for NER for ULMFiT
Deep learning (DL) approaches use various processing layers to learn hierarchical representations of data. Recently, many methods and designs of natural language processing (NLP) models have shown significant development, especially in text mining and analysis. For learning vector-space representations of text, there are famous models like Word2…
Review materials for the TWiML Study Group. Contains annotated versions of the original Jupyter noteboooks (look for names like *_jcat.ipynb ), slide decks from weekly Zoom meetups, etc.
AWD-LSTM and ULMFiT reproduction from scratch
Flask based application using to detect depression for transcripts of interviews from patients
Pre-trained AWD-LSTM language model trained on Filipino text corpus using fastai v2. Instructions included.
ULMFiT language model for Czech language
Applying a semi-supervised ULMFiT model to Twitter US Airlines Sentiment.
👩🏫 Pre-trained German Language Model with sub-word tokenization for ULMFIT
Method Development for Predicting Protein Subcellular Localization Based on Deep Learning
Multi-Label Text Classification with Transfer Learning
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