Is the trick of initializing with real tokens the secret to making all prefix tuning approaches competitive? BTW @EyubogluSabri I don't see DoRA mentioned in your paper – I wonder if that would close the gap a bit?
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LoRA vs DoRA vs Prefix Tuning: Fine-tuning Method Effectiveness
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The big open question for me is why LoRA (and particularly DoRA) has been the most successful for fine-tuning, but it worked so badly for this use case. Or maybe the opposite – why did prefix tuning work so well?
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Stable Diffusion 3.5 Models Now Available for Commercial Use
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The optimized models are now available for commercial and non-commercial use under the permissive Stability AI Community License. Weights and code @Huggingface
: https://
huggingface.co/collections/st
abilityai/stable-diffusion-35-671785cca799084f71fa2838
… @Github
: https://
github.com/NVIDIA/TensorR
T/tree/release/10.11/demo/Diffusion
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Databricks Summit: Hands-On AI Agent and Data Labs
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At #DataAISummit this week, attendees took part in hands-on labs across a range of technical sessions—gaining practical experience and leveling up their skills on the Databricks platform. Here’s a quick look at what they learned: AI Agent Workflows AI-Powered Data
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Fast JAX Implementations Delivering State-of-the-Art TPU Performance
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These implementations are very fast — when run with JAX, you'll get state of the art performance. And they all run on TPUs.
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KerasHub: 70+ Pretrained Models Supporting JAX, TF, PyTorch
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KerasHub is a collection of over 70 popular pretrained model architectures — LLMs, VLMs, image generation models, etc — that work with JAX, TF, PyTorch. They all support HuggingFace checkpoints — you can load any HF model with them for the corresponding architecture.
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Deployment Failure Mystery Solved After Hour
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We were deploying a new version exactly an hour or two ago and couldn't figure out why it failed every single time, now we know
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12 Essential Machine Learning Algorithms You Should Know
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Want to build real ML solutions? Here are 12 essential #MachineLearning algorithms you should know: 1. Naive Bayes
2. SVM
3. Decision Trees
4. K-Means
5. Linear/Logistic Regression
6. PCA
7. Random Forest
8. Q Learning
9. Dimensionality Reduction
…and more! Save this
