Introduction to tuning pre-trained transformer models | by Ram Vegiraju | February 2024
Simplified using the HuggingFace training objectPicture of unpack by Markus SpiskeHugsFace It serves as the home for many popular open ...
Tag: PreTrained
Google DeepMind introduces MusicRL: a pre-trained autoregressive MusicLM model of discrete audio tokens fine-tuned with reinforcement learning to maximize sequence-level rewards
In the fascinating world of artificial intelligence and music, a team at Google DeepMind has taken an innovative step. His ...
Google Research introduces TimesFM: a unique forecasting model pre-trained on a large time series corpus of 100 billion real-world time points
Time series forecasting is an important task in machine learning and is frequently used in various fields such as finance, ...
Large Language Models, GPT-1 — Generative Pre-Trained Transformer | by Vyacheslav Efimov | Jan, 2024
Diving deeply into the working structure of the first version of gigantic GPT-models2017 was a historical year in machine learning. ...
Tensoic AI launches Kan-Llama: a LoRA 7B Llama-2 pre-trained and tuned in 'Kannada' tokens
Tensoic has recently introduced Kannada Call (Kan-LLaMA) to address the limitations of language models (LLMs), specifically focusing on proprietary characteristics, ...
Pre-trained language models do not help autoregressive text-to-image generation
This work was accepted in the workshop. I can't believe it's not better! (ICBINB) at NeurIPS 2023. Recent advances in ...
This AI article from Google DeepMind studies the gap between pre-training data composition and in-context learning in pre-trained transformers
Google DeepMind researchers explore the in-context learning (ICL) capabilities of large language models, specifically transformative ones, trained on various task ...
Are you doing recovery augmented generation (RAG) for biomedicine? Meet MedCPT: A Pre-Trained Contrastive Transformative Model for Zero-Shot Biomedical Information Retrieval
Information retrieval (IR) models have the ability to sort and classify documents based on user queries, facilitating efficient and effective ...
Researchers in China introduced a new compression paradigm called retrieval-based knowledge transfer (RetriKT): revolutionizing the deployment of large-scale pre-trained language models in real-world applications
Natural Language Processing (NLP) applications have shown remarkable performance using pre-trained language models (PLM), including BERT/RoBERTa. However, due to their ...
Meet ScaleCrafter: Unlocking Ultra-High Resolution Image Synthesis with Pre-Trained Diffusion Models
The development of image synthesis techniques has experienced a notable boom in recent years, arousing great interest in academia and ...
Recommended.
