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Xiaohua Zhai on Twitter: "Locked-image Tuning (LiT🔥) is an alternative method to fine-tuning. It turns any pre-trained vision backbone to a zero-shot learner! LiT achieves 84.5% 0-shot acc. on ImageNet and 81.1%
LiT: Zero-Shot Transfer with Locked-image Tuning
Akshay 🚀 on Twitter: "Fine-tune GPT Like LLMs on a Custom Dataset! 🔥 Introducing LitParrot! 🚀 Fresh out of the cage: - nanoGPT based💡 - Hackable 🛠️ - With pre-training/fine-tuning script 📜
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LiT: Zero-Shot Transfer with Locked-image Tuning
Brief Review — LiT: Zero-Shot Transfer with Locked-image text Tuning | by Sik-Ho Tsang | Medium
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GitHub - Lightning-AI/lit-gpt: Hackable implementation of state-of-the-art open-source LLMs based on nanoGPT. Supports flash attention, 4-bit and 8-bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed.
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Locked-Image Tuning: Adding Language Understanding to Image Models – Google Research Blog
Xiaohua Zhai on Twitter: "Locked-image Tuning (LiT🔥) is an alternative method to fine-tuning. It turns any pre-trained vision backbone to a zero-shot learner! LiT achieves 84.5% 0-shot acc. on ImageNet and 81.1%
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LiT: Zero-Shot Transfer with Locked-image text Tuning | Papers With Code
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Locked-Image Tuning: Adding Language Understanding to Image Models – Google Research Blog
