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Found 4 papers, 4 papers with code
OpenAssistant Conversations -- Democratizing Large Language Model Alignment
In an effort to democratize research on large-scale alignment, we release OpenAssistant Conversations, a human-generated, human-annotated assistant-style conversation corpus consisting of 161, 443 messages in 35 different languages, annotated with 461, 292 quality ratings, resulting in over 10, 000 complete and fully annotated conversation trees.
Reproducible scaling laws for contrastive language-image learning
To address these limitations, we investigate scaling laws for contrastive language-image pre-training (CLIP) with the public LAION dataset and the open-source OpenCLIP repository.
Ranked #1 on
Zero-Shot Image Classification
on Country211
(using extra training data)
LAION-5B: An open large-scale dataset for training next generation image-text models
We show successful replication and fine-tuning of foundational models like CLIP, GLIDE and Stable Diffusion using the dataset, and discuss further experiments enabled with an openly available dataset of this scale.
LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs
Multi-modal language-vision models trained on hundreds of millions of image-text pairs (e. g.
