Bereket A. Yilma's repositories
AI-Expert-Roadmap
Roadmap to becoming an Artificial Intelligence Expert in 2022
LLM-Finetuning
LLM Finetuning with peft
giskard
🐢 The testing framework for ML models, from tabular to LLMs
LLM-scientific-feedback
Can large language models provide useful feedback on research papers? A large-scale empirical analysis.
gsasrec
code for the gsasrec paper
opendata
The National Gallery of Art Open Data Program
MRL_VA_RecSys
Together Yet Apart: Multimodal Representation Learning for Personalised Visual Art Recommendation
Awesome-Multimodal-Large-Language-Models
Latest Papers and Datasets on Multimodal Large Language Models
VSC22-Submission
[CVPR 2023 Workshop] The code reproduce the results of our solutions on both tracks for Meta AI Video Similarity Challenge (CVPR 2023 Workshop). Our solutions got the first place on both tracks, including Descriptor Track and Matching Track.
ImageBind
ImageBind One Embedding Space to Bind Them All
pandas-ai
Pandas AI is a Python library that integrates generative artificial intelligence capabilities into Pandas, making dataframes conversational
gesture_augmentation
Data augmentation for stroke gestures
the-algorithm
Source code for Twitter's Recommendation Algorithm
Multi-Stakeholder_RecSys
Personalisation in Cyber-Physical-Social Systems: A Multistakeholder aware Recommendation and Guidance in National Gallery
Personalized-Visual-Art-Recommendation
Personalized Visual Art Recommendation by Learning Latent Semantic Representations
llama
Inference code for LLaMA models
openTSNE
Extensible, parallel implementations of t-SNE
ToMe
A method to increase the speed and lower the memory footprint of existing vision transformers.
PaLM-rlhf-pytorch
Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM
tuning_playbook
A playbook for systematically maximizing the performance of deep learning models.
LAVIS
LAVIS - A One-stop Library for Language-Vision Intelligence
RecSys-an-overview
Recommender Systems: an overview[Course_materials]; Doctoral education programme in Computer Science and Computer Engineering at University of Luxembourg.
lm-human-preferences
Code for the paper Fine-Tuning Language Models from Human Preferences