Fine-tuning Llama2-7b and other llms for categorising emails for Deutsche Bahn (German National Railways)
-
Updated
Oct 9, 2023 - Jupyter Notebook
Fine-tuning Llama2-7b and other llms for categorising emails for Deutsche Bahn (German National Railways)
How to deploy a BERT model from Hugging Face Model Hub to Amazon SageMaker for a Fill-Mask use case.
Text auto-completion system using the bert-base-uncased model by Hugging Face in the backend. Designed to enhance user experience across various applications, it anticipates and suggests word sequences as users type.
Text auto-completion system using the bert-base-uncased model by Hugging Face in the backend. Designed to enhance user experience across various applications, it anticipates and suggests word sequences as users type.
Analyse sentiments from youTube (comments) with MLFlow!
Proof of Concept for a Machine Learning Classification Model using a custom 'bert-base-uncased' model.'
Multi-model duplicate question classifier for Quora dataset. Implements three architectures: (1) XGBoost with Word2Vec + fuzzy matching features, (2) PyTorch BiLSTM with early stopping, and (3) Fine-tuned BERT for sequence classification. Complete pipeline from preprocessing to inference.
Add a description, image, and links to the bert-base-uncased topic page so that developers can more easily learn about it.
To associate your repository with the bert-base-uncased topic, visit your repo's landing page and select "manage topics."