Trending Research
LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention
zrrskywalker/llama-adapter
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We present LLaMA-Adapter, a lightweight adaption method to efficiently fine-tune LLaMA into an instruction-following model.
ChatDoctor: A Medical Chat Model Fine-tuned on LLaMA Model using Medical Domain Knowledge
Recent large language models (LLMs) in the general domain, such as ChatGPT, have shown remarkable success in following instructions and producing human-like responses.
Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators
picsart-ai-research/text2video-zero
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Recent text-to-video generation approaches rely on computationally heavy training and require large-scale video datasets.
Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation
To replicate the success of text-to-image (T2I) generation, recent works employ large-scale video datasets to train a text-to-video (T2V) generator.
PAniC-3D: Stylized Single-view 3D Reconstruction from Portraits of Anime Characters
shuhongchen/panic3d-anime-reconstruction
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We propose PAniC-3D, a system to reconstruct stylized 3D character heads directly from illustrated (p)ortraits of (ani)me (c)haracters.
P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks
huggingface/peft
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Prompt tuning, which only tunes continuous prompts with a frozen language model, substantially reduces per-task storage and memory usage at training.
Exploring the Impact of Instruction Data Scaling on Large Language Models: An Empirical Study on Real-World Use Cases
However current research rarely studies the impact of different amounts of instruction data on model performance, especially in the real-world use cases.
Colossal-Auto: Unified Automation of Parallelization and Activation Checkpoint for Large-scale Models
To address these challenges, we introduce a system that can jointly optimize distributed execution and gradient checkpointing plans.
Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior
In this work, we investigate the problem of creating high-fidelity 3D content from only a single image.
SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models
BlinkDL/RWKV-LM
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We propose SmoothQuant, a training-free, accuracy-preserving, and general-purpose post-training quantization (PTQ) solution to enable 8-bit weight, 8-bit activation (W8A8) quantization for LLMs.
