AI · alternatives · 2026

24 alternatives to I invented a new generative model and got accepted to ICLR

I invented Discrete Distribution Networks, a novel generative model with simple principles and unique properties, and the paper has been accepted to ICLR2025! Modeling data distribution is challenging; DDN adopts a simple yet fundamentally different approach compared to mainstream generative models (Diffusion, GAN, VAE, autoregressive model): 1. The model generates multiple outputs simultaneously in a single forward pass, rather than just one output. 2. It uses these multiple outputs to approximate the target distribution of the training data. 3. These outputs together represent a discrete…

Discrete Distribution Networks is a generative model that produces multiple outputs simultaneously in a single forward pass to approximate data distributions, offering a fundamentally different approach from diffusion… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.

1
Tiny Diffusion – A character-level text diffusion model from scratch▲172
I previously posted this a month and a half ago: https://news.ycombinator.com/item?id=45876742 I have rewritten it to be much more simple, from 951 lines of code to just 364, with no loss in core functionality or generation quality. I also added a tiny GPT implementation as a comparison (inspired by Andrej Karpathy's code). The two model implementations are ~80% identical, with the core differences being the generate and get_batch functions. The model architecture, training loop, etc, differ in only 19 lines of code. Trained weights are included, so you can just clone and run…
Nov 2025 · github.com · its alternatives →
2
I built a tiny LLM to demystify how language models work▲915
Built a ~9M param LLM from scratch to understand how they actually work. Vanilla transformer, 60K synthetic conversations, ~130 lines of PyTorch. Trains in 5 min on a free Colab T4. The fish thinks the meaning of life is food. Fork it and swap the personality for your own character.
Apr 2026 · github.com · its alternatives →
3
InvokeAI, an open source Stable Diffusion toolkit and WebUI▲414
Hey everyone! Excited to be able to share the release of `InvokeAI 2.0 - A Stable Diffusion Toolkit`, an open source project that aims to provide both enthusiasts and professionals a suite of robust image creation tools. Optimized for efficiency, InvokeAI needs only ~3.5GB of VRAM to generate a 512x768 image (and less for smaller images), and is compatible with Windows/Linux/Mac (M1 & M2). InvokeAI was one of the earliest forks off of the core CompVis repo (formerly lstein/stable-diffusion), and recently evolved into a full-fledged community driven and open source stable…
2022 · github.com · its alternatives →
4
Create your own video clips with Stable Diffusion▲247
A few months ago, I started making video clips with stable diffusion and noticed that the tools to do this were too complicated for everyday people. That's why I built neural frames. Enjoy.
2023 · neuralframes.com · its alternatives →
5
Open Prompts – dataset of 10M Stable Diffusion generations▲279
Open Prompts is the dataset used to build krea.ai. The data comes from the Stability AI Discord and includes around 10M images from 2M prompts. You can use it for creating semantic search engines of prompts, training LLMs, fine-tuning image-to-text models like BLIP, or extracting insights from the data—like the most common combinations of modifiers.
2022 · github.com · its alternatives →
6
AI Video Generator by Gan.AI▲229
The easiest way to produce professional videos from Scripts
2025 · its alternatives →
7
I trained a neural network to write Kanji▲166
sketch-rnn model trained to write kanji.
2018 · otoro.net · its alternatives →
8ND
[NSFW] Diffusion models for porn generation▲40
2022 · orchid.gistnoesis.net · its alternatives →
9
Ideogram 4.0 – open-weight 9.3B text-to-image model▲46
It's our new text-to-image model: a 9.3B single-stream diffusion transformer trained entirely from scratch. We focused heavily on controllability through structured JSON prompts, with strong text rendering, spatial awareness through bounding box guidance, and color palette control. It has the best text rendering of any open-weight model we've tested so far, and the NF4 quantized checkpoint runs on a single 24GB GPU. For more technical details and examples see our blog post: https://ideogram.ai/blog/ideogram-4.0/ We will be happy to answer any questions :)
Jun 2026 · github.com · its alternatives →
10
Image Pipeline▲143
Multi Model Stable Diffusion Pipelines
2023 · imagepipeline.io · its alternatives →
11
Fine-grained stylistic control of LLMs using model arithmetic▲85
We developed a new framework that enables flexible control of generated text in language models. By combining several models and/or system prompts in one mathematical formula, it lets you tweak your style and combine model outputs with ease. A handy tool for those working with LLMs, looking for more fine-grained control of stylistic output. More details in our paper: https://arxiv.org/abs/2311.14479. Feedback and potential applications are welcome.
2023 · github.com · its alternatives →
12
Stable Diffusion Model▲109
Generate AI art for free
2023 · its alternatives →
13AV
A Visual and Interactive Guide to the Basics of Neural Networks▲63
Discussions: Hacker News (63 points, 8 comments), Reddit r/programming (312 points, 37 comments) Translations: Arabic, French, Spanish Update: Part 2 is now live: A Visual And Interactive Look at Basic Neural Network Math Motivation I’m not a machine learning expert. I’m a software engineer by train
2016 · jalammar.github.io · its alternatives →
14
Modular Diffusion – A modular Python library for diffusion models▲40
Hello everyone! I've been working on this project for a few months as part of my thesis in Machine Learning. It's meant to be a library that provides an easy-to-use but flexible API to design and train Diffusion Models. I decided to make it because I wanted to quickly prototype a Diffusion Model but there were no good tools to do it with. I think it really can help people prototype their own Diffusion Models a lot faster and only in a few lines of code. The base idea is to have a Model class that takes different modules corresponding to the different aspects of the Diffusion Model process…
2023 · github.com · its alternatives →
15
Implementation of DDPM (Denoising Diffusion Probabilistic Models)▲10
Just small prototype showcasing diffusion models
2025 · github.com · its alternatives →
16
Stable Diffusion 3▲72
Open-weights generative AI model for image synthesis
2024 · stability.ai · its alternatives →
17SD
Stable Diffusion Without Filters▲52
2022 · healthydiffusion.com · its alternatives →
18
Stable Diffusion v2 web interface▲72
Design unique visuals with our Text to Image AI tool. Generate beautiful, custom images from your text prompts, with options for various styles.
2022 · getimg.ai · its alternatives →
19TY
Train your own image generator (Stable Diffusion) for free▲35
I've had a blast playing with stable diffusion and I see all the potential it will bring to us. I released a service for training your model, just upload 20-30 images and you can have a model of someone or some object doing anything. You can train one model for free a month in a slower queue or you can train many models on a fast queue and with other features for a fee. Here is an example of using it for show product placement: https://app.88stacks.com/image/O6kReClOvrz7 and here is an example of using it for people:…
2022 · 88stacks.com · its alternatives →
20IP
I published 100 AI generated books on Amazon▲20
To be specific, the content is generated by a GPT-2 based model. https://amzn.to/2TCc0v2 Let me know if you have any questions :-)
2020 · its alternatives →
21LR
Linear RNN/Reservoir hybrid generative model, one C file (no deps.)▲7
I just noticed it takes literally ~5 minutes to train millions parameters on slow CPU...but before you call Yudkowsky that "it's over", an important note: the main bottleneck is the corpus size, params are just 'cleverness' but given limited info it's powerless. Anyway, here is the project: https://github.com/bggb7781-collab/lrnnsmdds/tree/main couple of notes: 1. single C file, no dependencies. Below are literally all the "dependencies", not even custom header (copy paste from the top of the single c file): #define _POSIX_C_SOURCE 200809L #include #include…
Apr 2026 · raw.githubusercontent.com · its alternatives →
22FS
Free Stable Diffusion 2.0 hosted interface▲25
Deploy and serve machine learnings models performantly, scalably, and cost-efficiently with Baseten.
2022 · app.baseten.co · its alternatives →
23
A first try to implement a Deep Learning model▲7
A repo of several notebooks and related resources where I run some experiments related to Machine Learning - dl-experiments/income-prediction/Predicting Income, A NN approach.ipynb at master · rcshubhadeep/dl-experiments
2017 · github.com · its alternatives →
24
Next-Gen AI Training: LLM-RLHF-Tuning with PPO and DPO▲30
Comprehensive toolkit for Reinforcement Learning from Human Feedback (RLHF) training, featuring instruction fine-tuning, reward model training, and support for PPO and DPO algorithms with various configurations for the Transformer 5 models including Qwen 3.0 - raghavc/LLM-RLHF-Tuning-with-PPO-and-DP
2024 · github.com · its alternatives →

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