* 4 new video models * Multiple image models, including SANA & Flux Control * New quantizers -> GGUF & TorchAO * New training scripts Enjoy this holiday-special Diffusers release 🤗 Notes: https://github.com/huggingface/diffusers/releases/tag/v0.32.0
In the past seven days, the Diffusers team has shipped:
1. Two new video models 2. One new image model 3. Two new quantization backends 4. Three new fine-tuning scripts 5. Multiple fixes and library QoL improvements
Coffee on me if someone can guess 1 - 4 correctly.
Introducing the Synthetic Data Generator, a user-friendly application that takes a no-code approach to creating custom datasets with Large Language Models (LLMs). The best part: A simple step-by-step process, making dataset creation a non-technical breeze, allowing anyone to create datasets and models in minutes and without any code.
How do your annotations for FineWeb2 compare to your teammates'?
I started contributing some annotations to the FineWeb2 collaborative annotation sprint and I wanted to know if my labelling trends were similar to those of my teammates.
I did some analysis and I wasn't surprised to see that I'm being a bit harsher on my evaluations than my mates 😂
Do you want to see how your annotations compare to others? 👉 Go to this Gradio space: nataliaElv/fineweb2_compare_my_annotations ✍️ Enter the dataset that you've contributed to and your Hugging Face username.
Quick update from week 1 of smol course. The community is taking the driving seat and using the material for their own projects. If you want to do the same, join in!
- we have ongoing translation projects in Korean, Vietnamese, Portuguese, and Spanish - 3 chapters are ready for students. On topics like, instruction tuning, preference alignment, and parameter efficient fine tuning - 3 chapters are in progress on evaluation, vision language models, and synthetic data. - around 780 people have forked the repo to use it for learning, teaching, sharing.
⏭️ Next step is to support people that want to use the course for teaching, content creation, internal knowledge sharing, or anything. If you're into this. Drop an issue or PR