This AI article from SambaNova presents a machine learning method to adapt pre-trained LLMs to new languages
The rapid advancement of large language models has ushered in a new era of natural language processing capabilities. However, a ...
Tag: PreTrained
Meet BiLLM: a novel post-training binary quantization method designed specifically to compress pre-trained LLMs
Pretrained large language models (LLMs) have remarkable language processing capabilities, but require substantial computational resources. Binarization, which reduces model weights ...
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 ...
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 ...
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