"Open Source Models with Hugging Face" course empowers you with the skills to leverage open-source models from the Hugging Face Hub for various tasks in NLP, audio, image, and multimodal domains.
-
Updated
Mar 6, 2024 - Jupyter Notebook
"Open Source Models with Hugging Face" course empowers you with the skills to leverage open-source models from the Hugging Face Hub for various tasks in NLP, audio, image, and multimodal domains.
Spam Detector is a Data Science Project built using Pytorch and Hugging Face library. Used BERT model based on Transformer Architecture and got 99.97% accuracy on train set and 98.76% accuracy on test set.
With the use of AI, summarise your movies and bring back the colour in older films.
Summarize, , NSP answer questions in dockerised environment
Successfully established a Seq2Seq with attention model which can perform English to Spanish language translation up to an accuracy of almost 97%.
Source codes and materials of Advanced Spelling Error Correction project.
llm-newsletter-generator transforms a valid RSS feed into a "Newsletter" using AI models via PyTorch and Transformers; this is experimental.
With the use of AI, summarise your movies and bring back the colour in older films.
NLP project: Text summarization application
Successfully developed a fine-tuned BERT transformer model which can accurately classify symptoms to their corresponding diseases upto an accuracy of 89%.
Successfully developed a fine-tuned DistilBERT transformer model which can accurately predict the overall sentiment of a piece of financial news up to an accuracy of nearly 81.5%.
A Python-based REST API for PDF OCR using AI models with PyTorch and Transformers that runs in a Docker container.
Add a description, image, and links to the hugging-face-transformers topic page so that developers can more easily learn about it.
To associate your repository with the hugging-face-transformers topic, visit your repo's landing page and select "manage topics."