LLaVA: Bringing Visual Fine-tuning to Large Models - Code World

LLaVA: Bringing Visual Fine-tuning to Large Models

News 2023-07-30 09:35:43 views: null

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Origin blog.csdn.net/weixin_44839084/article/details/131857065

LLaVA: Bringing Visual Fine-tuning to Large Models

A Survey of Fine-tuning Methods for Large Models

Summary of fine-tuning techniques for large models

【ChatGLM】ChatGLM fine-tuning of large models

Efficient fine-tuning technology for large models

[Instruction fine-tuning of LLM series] Long story short, "Prompt" for instruction fine-tuning of large models

Efficient fine-tuning of large models - introduction to the PEFT framework

Practical tips for fine-tuning large language models with LoRA

Summary of three fine-tuning techniques for pre-training large language models: fine-tuning, parameter-efficient fine-tuning and prompt-tuning

Summary of fine-tuning methods for large models: LoRA, Adapter, Prefix-tuning, P-tuning, Prompt-tuning

In the era of AIGC, how can fine-tuning of large models play the most important role?

LoRA: A Low-Rank Adaptive Fine-tuning Model for Large Models

Under the overview of efficient fine-tuning of large models: DiffPruning, BitFit, LoRa, AdaLoRA, MAM Adapters, UniPELT

Full-parameter fine-tuning of large language models with limited resources

[AI] Algorithm cheat sheet - summarizing the fine-tuning method of large models

[Natural Language Processing] Efficient fine-tuning of large models: PEFT use cases

Bloom&LLAMA of large models----SFT (model fine-tuning)

Fine-tuning large models via WiSE-FT (catastrophic forgetting)

LLM fine-tuning (3) | Analysis of RLHF + Reward Model + PPO technology in large models

The secret weapon for efficient development of large models: MindSpore PET, a low-parameter fine-tuning kit for large models

On the overview of efficient fine-tuning of large models: Adapter Tuning, AdaMix, PET, Prefix-Tuning, Prompt Tuning, P-tuning, P-tuning v2

Practical application of large models 10 - Detailed explanation of large model domain knowledge and parameter efficient fine-tuning (PEFT) technology, and use PEFT to train your own large models

Interpretation of Lawyer LLaMA, fine-tuning of large models in Yanshen's professional field: data set construction, model training

Popular understanding of major fine-tuning methods for large models: from Prefix Tuning, P-Tuning V1/V2 to LoRA, QLoRA

NLP large model fine-tuning principle

Fudan Qiu Xipeng's new work: single-machine fine-tuning of a large model with 65 billion parameters, industry insiders: it is of great significance to the popularization of large models...

From instruction fine-tuning to mathematical reasoning capabilities, explore the potential of large models | The 11th issue of the large model series activities on September 14

【LLM】Prompt tuning large model fine-tuning practice

Large language model fine-tuning and PEFT efficient fine-tuning

LLMs: LLaMA Efficient Tuning (an efficient tool that can efficiently fine-tune [full parameters/LoRA/QLoRA] mainstream large models [ChatGLM2/LLaMA2/Baichuan, etc.] [pre-training + instruction supervision fine-tuning +

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