QLoRA finetunes 4-bit quantized LLMs via LoRA adapters to match full-precision performance while using far less memory, enabling 65B-scale training on single GPUs and producing Guanaco models near ChatGPT level.
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ModernBERT is a new bidirectional encoder model achieving SOTA performance on diverse classification and retrieval benchmarks while offering superior speed and memory efficiency for long-context inference.
Three BERT models are further pre-trained on Norwegian clinical notes and discharge summaries, then shown to outperform their base models on synthetic clinical benchmarks and real-world tasks.
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QLoRA: Efficient Finetuning of Quantized LLMs
QLoRA finetunes 4-bit quantized LLMs via LoRA adapters to match full-precision performance while using far less memory, enabling 65B-scale training on single GPUs and producing Guanaco models near ChatGPT level.
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Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference
ModernBERT is a new bidirectional encoder model achieving SOTA performance on diverse classification and retrieval benchmarks while offering superior speed and memory efficiency for long-context inference.
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KliniskVestBERT: BERT Model Specialised to Norwegian Clinical Texts
Three BERT models are further pre-trained on Norwegian clinical notes and discharge summaries, then shown to outperform their base models on synthetic clinical benchmarks and real-world tasks.