Fine-tuning Gemma Models with PEFT and LoRA Using HuggingFace Datasets
Master parameter-efficient fine-tuning techniques for Gemma 2B model using PEFT and LoRA, with hands-on code implementation and custom dataset creation for optimized model training.
Supercharging Multi-LLM Intelligence with CALM - Composition to Augment Language Models
Discover how CALM (Composition to Augment Language Models) revolutionizes multi-LLM integration through advanced projection layers and cross-attention mechanisms for enhanced AI capabilities.
Diffusion Transformer and Rectified Flow in Stable Diffusion 3
Dive into the mechanics of Diffusion Transformers, exploring noise distribution, latent space dimensionality, and the innovative Rectified Flow technology powering next-gen AI image generation.
Understanding 4-bit Quantization and QLoRA - Memory Efficient Fine-tuning of LLMs
Dive into memory-efficient fine-tuning of large language models through 4-bit quantization and QLoRA, combining theoretical foundations with practical implementation in Colab.
Parameter Efficient Fine-Tuning with Multiple LoRA Adapters for Large Language Models
Dive into parameter efficient fine-tuning with LoRA adapters, exploring matrix factorization, SVD, and advanced configurations for optimizing large language models.
QLoRA: Efficient Training of Large Language Models Using Quantization and Low-Rank Adaptation
Discover how QLoRA enables efficient training of large language models on a single GPU through innovative techniques like NormalFloat, Double Quantization, and Paged Optimizers.
LoRA: Low-Rank Adaptation for Parameter-Efficient Large Language Model Fine-Tuning
Discover how LoRA enables efficient fine-tuning of large language models through low-rank adaptation, from fundamental concepts to practical implementation in transformer architectures.
ControlNet: Adding Conditional Control to Text-to-Image Diffusion Models
Delve into the groundbreaking ControlNet paper, exploring its architecture, classifier-free guidance, and spatial control capabilities in text-to-image diffusion models through detailed technical explanations.
LoftQ: Understanding LoRA-Fine-Tuning-aware Quantization for LLMs
Dive into LoftQ, a groundbreaking LLM quantization method that combines with LoRA to achieve superior performance and efficiency in large language models.
Stable Diffusion XL with T2I-Adapter and ControlLoRA - Tutorial and Demo
Master advanced image generation techniques using SDXL with T2I adapters and ControlLoRA, featuring hands-on demonstrations and practical implementations for enhanced AI art creation.
Fine-tuning LLama 2 with PEFT, LoRA, 4-bit Quantization, TRL and SFT
Master advanced LLama2 fine-tuning techniques using PEFT, LoRA, and 4-bit quantization while creating synthetic datasets with GPT-4 for customized model training.
Stanford ALPACA 7B LLM: Fine-tuning Guide with Code and Datasets
Discover how to fine-tune and implement Stanford's ALPACA 7B language model using LLaMA, exploring practical applications and cost-effective methods for creating custom AI solutions.
Optimizing LLM Fine-Tuning with PEFT and LoRA Adapter-Tuning for GPU Performance
Master efficient fine-tuning of large language models using PEFT and LoRA techniques, optimizing GPU memory usage through INT8 quantization and adapter-tuning for cost-effective model development.
Parameter-Efficient Fine-Tuning with LoRA - Optimizing LLMs for Local GPU Training
Master PEFT LoRA techniques to efficiently fine-tune large language models on local GPUs through low-rank adaptation, reducing memory requirements while maintaining model performance.
Improving Stable Diffusion Images with FreeU - Optimizing SDXL, LCM, and Turbo Models
Optimize Stable Diffusion images using FreeU hyperparameters. Learn to leverage ComfyUI API for grid searching ideal parameters in SDXL, LCM, and Turbo models. Practical demonstrations and comparisons included.
Stable Diffusion - Building Amazing Images with AI
Explore Stable Diffusion AI for image creation, covering embeddings, diffusion models, and practical examples. Learn to generate stunning visuals from text prompts.
Explaining Stable Diffusion for Machine Learning Engineers
Dive deep into stable diffusion concepts, exploring diffusion models, training processes, text conditioning, and latent diffusion for machine learning engineers.
Zephyr LPWAN Connectivity Options and When to Choose Them
Explore LPWAN technologies supported by Zephyr, comparing their advantages and trade-offs for power, range, and reachability. Learn to choose the best option for your IoT project.
Flux Inpainting - Ultimate Guide
Master flux inpainting techniques using Forge UI for Stable Diffusion and other models. Learn advanced methods to enhance and manipulate AI-generated images effectively.
Stable Diffusion - Master AI Art: Installation, Prompts, Txt2img-Img2img, Out-Inpaint and Resize Tutorial
Comprehensive tutorial on Stable Diffusion AI art generation, covering installation, prompts, text-to-image, image-to-image, outpainting, inpainting, and advanced techniques for creating diverse AI-generated artwork.
Get Started With Stable Diffusion - Code, HF Spaces, Diffusers Notebooks
Learn three methods to use Stable Diffusion: HuggingFace Spaces, Colab notebooks, and local setup. Gain practical skills in image generation, metadata reproduction, and interpolation techniques.