fake-news
mt5-M2M-comparison
| fake-news | mt5-M2M-comparison | |
|---|---|---|
| 1 | 1 | |
| 130 | 13 | |
| - | - | |
| 4.1 | 3.8 | |
| over 3 years ago | almost 3 years ago | |
| Jupyter Notebook | Jupyter Notebook | |
| GNU Affero General Public License v3.0 | - |
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fake-news
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Building an End-to-End Machine Learning Application From Idea to Deployment
Hi I had the same issue I think code for EDA part is in https://github.com/mihail911/fake-news/blob/master/notebooks/data_analysis.ipynb
mt5-M2M-comparison
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[D] Comparing M2M to mT5 in low resource translation (10k dataset Yoruba - English)
I found no clear comparison nor a clear guide on how to fine tune both of the models on the translation task, so I decided to write it myself. (code: https://github.com/maroxtn/mt5-M2M-comparison)
What are some alternatives?
onepanel - The open source, end-to-end computer vision platform. Label, build, train, tune, deploy and automate in a unified platform that runs on any cloud and on-premises.
fastT5 - ⚡ boost inference speed of T5 models by 5x & reduce the model size by 3x.
fastMONAI - Simplifying deep learning for medical imaging
keytotext - Keywords to Sentences
mlf-core - CPU and GPU deterministic and therefore fully reproducible machine learning pipelines using MLflow.
OpenNMT-Tutorial - Neural Machine Translation (NMT) tutorial. Data preprocessing, model training, evaluation, and deployment.
bert-sklearn - a sklearn wrapper for Google's BERT model
100DaysOfML - 100 Days Of Machine Learning. New Content in every 1-2 day and projects every week. The massive 100DaysOfML in building
peacasso - UI interface for experimenting with multimodal (text, image) models (stable diffusion).
question_generation - Neural question generation using transformers
TabularSemanticParsing - Translating natural language questions to a structured query language