---
title: "Hugging Face"
description: "2 posts about Hugging Face, summarised, each linking to the original."
---

# Hugging Face
> 2 posts about Hugging Face, summarised, each linking to the original.

## Articles

### [Welcome FLUX.3 Image Klein in Diffusers](https://yomu.fyi/post/welcome-flux-3-image-klein-in-diffusers.md)
- Company: [Hugging Face](https://yomu.fyi/company/hugging-face.md)
- Author: Aritra Roy Gosthipaty, Sayak Paul, Linoy Tsaban
- Published: Oct 15, 2026
- Type: Announcement

The Black Forest Labs FLUX.3 Image Klein model is now available in Diffusers, combining text-to-image, multi-reference image-to-image, and bounding-box layout control into one pipeline. Two open checkpoints are offered: a distilled version using 16 inference steps without classifier-free guidance for fast generation, and a base version requiring 50 steps with guidance. The distilled checkpoint produces a 1024x1024 image in about two seconds on an H100, and quantized NVFP4 and FP8 weights can be loaded via from\_single\_file to reduce memory. The model is built as a Modular Diffusers pipeline, enabling users to remove, replace, or insert custom components, such as a block that captures intermediate clean-image previews. LoRA fine-tuning scripts for both text-to-image and image editing are included, along with a prompting guide for optimal scene descriptions.


### [The model that didn't exist, so you made it yourself](https://yomu.fyi/post/the-model-that-didn-t-exist-so-you-made-it-yourself.md)
- Company: [Hugging Face](https://yomu.fyi/company/hugging-face.md)
- Author: yuvraj sharma, Abubakar Abid
- Published: Oct 8, 2026
- Type: Tutorial

The author wanted a small version of the prompt rewriter that ships with Qwen-Image 2.1, but the official 9B model requires about 20 GB of memory. Using ML Intern in HuggingChat, they created a 0.8B version that runs on a CPU, returns valid output 99.7% of the time, and uses about a quarter of the teacher’s tokens. The compute for the entire project, including having the 9B model label 8,797 example requests, came to USD 16. Over a few days, the author made five more models using the same approach, each starting as a message in HuggingChat with ML Intern switched on. The author’s prompts include verified facts, a baseline request, a smoke test, and a spending cap. The six models built include a citrus disease vision model, a Huggy character LoRA, a camera-angle LoRA, a doodle-in LoRA, a pocket rewriter, and a distilled text-to-image model.