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V-diffusion-pytorch Alternatives
Similar projects and alternatives to v-diffusion-pytorch
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stylegan2-pytorch
Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement
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InfluxDB
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RWKV-LM
RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.
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SaaSHub
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conceptual-12m
Conceptual 12M is a dataset containing (image-URL, caption) pairs collected for vision-and-language pre-training.
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SaaSHub
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NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better v-diffusion-pytorch alternative or higher similarity.
v-diffusion-pytorch reviews and mentions
Posts with mentions or reviews of v-diffusion-pytorch.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-04-23.
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Leaked deck raises questions over Stability AI’s Series A pitch to investors
This is dumb.
We employed Eleuther team members as Stability AI employees/contractors and incubated them until the 501(c)3 was set up and we managed to bring in other funders too: https://techcrunch.com/2023/03/02/stability-ai-hugging-face-...
I am on the board and delighted to continue to support their work as an independent organisation for LM evaluation, alignment and interpretability which is much needed.
Indeed though our approach was handing out significant compute for no control, no equity, no IP.
Anyone who has received Stability AI grants will be able to attest to this with multiple breakthroughs as a result, for example funding https://github.com/BlinkDL/RWKV-LM, the work of https://github.com/lucidrains and others.
Similarly we funded the beta of MidJourney with a cash grant for compute without ever even floating asking for equity etc as it is a market-creating innovation.
At the time MidJourney was using cc12m_1, a model developed by one of our lead (employed) generative AI developers Katherine Crownson / RiversHaveWings (https://github.com/crowsonkb/v-diffusion-pytorch)
Our model is simply to take open innovation and create commercial variants of that (our stable series models) from scratch and on our own, plus variants of that for private data - https://twitter.com/EMostaque/status/1649152422634221593?s=2...
This means we can be hands off versus other funders and trust researchers and help them succeed, something others do not.
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[D] Is Midjourney AI more-or-less the same architecture as DALL-E 2? Can I read about the model in detail somewhere or is there anything published in this regard?
From what I've gathered by being involved early in the beta / in other discords, Midjourney was originally based on a fine-tuned version of classifier-free guided v-diffusion. The fine-tuning dataset was a manually curated set largely from LAION-2B similar to the laion-art / laion-hd. To make it so fast they were using Progressive Distillation (possibly distilling on PLMS steps rather than p/ddim?) and settings optimized to let them skip a few of the first steps like Quick CLIP-Guided Diffusion. There's a good chance they were doing some prompt augmentation as well, although I think this would be susceptible to prompt discovery attacks which I haven't seen any examples of for Midjourney.
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Tweet: "Give us a few weeks, open version in the works." regarding an open Google Imagen-like system
Source. This tweet is from a person whose organization has been publicly credited with providing compute for others in the past (example: "Thank you to stability.ai for compute to train these models!").
- Does anyone know which GAN this is?
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Dall-E 2
com/RiversHaveWings/status/1462859669454536711, 2021.
[8] Katherine Crowson. v-diffusion. https://github.com/crowsonkb/v-diffusion-pytorch, 2021.
- How do I start creating my own AI generated art?
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Advice on improving Text to Image Model (CC12M Diffusion) model at higher output dimensions?
More parameters are available as seen in this code. The fix was adapted from this.
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Colab notebook "Text to Image (CC12M Diffusion)" from RiversHaveWings was updated with significantly faster image generation speed. It generates 4 images in 4.75 minutes (not including setup time) on a Tesla K80 GPU (free-tier Colab).
I'm not sure if this Colab notebook was mentioned in this sub previously, but it's been available since January 2022. The cc12m_1_cfg model used by this Colab notebook is different than the cc12m_1 model from this December 2021 post (reference).
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Airport carpets (a genurary submission)
A few more here https://twitter.com/metasemantic/status/1486334535436488705. Samples careful constructed with a heavily modified diffusion model by @rivershavewings https://github.com/crowsonkb/v-diffusion-pytorch
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Steampunk Airships
Most of the code was from Katherine Crowson's (@RiversHaveWings) v-diffusion-pytorch library (https://github.com/crowsonkb/v-diffusion-pytorch), which is an implementation of denoising diffusion probabilistic models (https://arxiv.org/abs/2006.11239). I used the CC12M_1 CFG checkpoint.
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A note from our sponsor - InfluxDB
www.influxdata.com | 8 May 2024
Stats
Basic v-diffusion-pytorch repo stats
10
690
0.0
over 1 year ago
crowsonkb/v-diffusion-pytorch is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of v-diffusion-pytorch is Python.
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