dalle-playground
dalle-flow
dalle-playground | dalle-flow | |
---|---|---|
35 | 31 | |
2,762 | 2,825 | |
- | 0.1% | |
3.2 | 2.3 | |
4 months ago | 12 months ago | |
JavaScript | Python | |
MIT License | - |
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dalle-playground
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Discord bot with a locally-hosted SD backend.
Built on dalle-playground because it is simple and I like it.
- Neural photo engine with Intel compute stick?
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Free/open-source AI Text-To-Image Models that can be run on AWS?
[1] https://github.com/saharmor/dalle-playground
- ai_irl
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Running Dall-e mini on Windows? (Or: Are there any equivalent text-to-image AI's I can run on a windows PC with a 2080 TI?)
If you decide to abandon the idea of running locally and want to run in the cloud instead, https://github.com/saharmor/dalle-playground has a Google Colab notebook that's relatively easy to run (although Google Colab's free tier is relatively limited).
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Run Your Own DALLĀ·E Mini (Craiyon) Server on EC2
Next, we want the code in the https://github.com/hrichardlee/dalle-playground repo, and we want to construct a pip environment from the backend/requirements.txt file in that repo. We were almost able to use the saharmor/dalle-playground repo as-is, but we had to make one change to add the jax[cuda] package to the requirements.txt file. In case you havenāt seen jax before, jax is a machine-learning library from Google, roughly equivalent to Tensorflow or PyTorch. It combines Autograd for automatic differentiation and XLA (accelerated linear algebra) for JIT-compiling numpy-like code for Googleās TPUs or Nvidiaās CUDA API for GPUs. The CUDA support requires explicitly selecting the [cuda] option when we install the package.
- Dream's over guys...
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How to run DALLE-2 locally
Is their any way to run DALLE-2 inside of a docker container similarly to this DALLE-PLAYGROUND repo on github?
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How difficult would it be to set up your own DALL-E (mini/mega) API for side-projects?
I know there are open source projects like dalle-playground. Would it literally be enough to host this app on an EC2 instance with the mini model?
- an AI image generator capable of taking a prompt and making it come to life.
dalle-flow
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How to Personalize Stable Diffusion for ALL the Things
Jina AI is really into generative AI. It started out with DALLĀ·E Flow, swiftly followed by DiscoArt. And thenā¦š¦š¦*š¦š¦. At least for a whileā¦
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image generation API similar to Dall-E or Dall-E 2
you can host your own https://github.com/jina-ai/dalle-flow
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[hlkyās/sd-webui] Announcing Sygil.dev & Project Nataili
For example for all the multimodal stuff like clipseg and upscalers, I'm using isolated executors through jina flow: https://github.com/jina-ai/dalle-flow/tree/main/executors
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Who needs prompt2prompt anyway? SD 1.5 inpainting model with clipseg prompt for "hair" and various prompts for different hair colors
clipseg is an image segmentation method used to find a mask for an image from a prompt. I implemented it as an executor for dalle-flow and added it to my bot yasd-discord-bot.
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Sequential token weighting invented by Birch-san@Github allows you to bypass the 77 token limit and use any amount of tokens you want, also allows you to sequentially alter an image
Merged into [dalle-flow](https://github.com/jina-ai/dalle-flow/pull/112) this morning and works on my Discord bot [yasd-discord-bot](https://github.com/AmericanPresidentJimmyCarter/yasd-discord-bot).
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I made a discord bot for artsy ML stuff - just finished integrating SD
https://github.com/jina-ai/dalle-flow with ports of some code from https://github.com/lstein/stable-diffusion plus some stuff specific to my uses (mostly more exposed settings and meta data on the outputs).
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AI generated picture "Beatles at Disneyland"
dalle flow - a more advanced version of dall-e mini, running dall-e mega and a diffusion model (free colab), free
- Comparison of DALL-E, Midjourney, Stable Diffusion and more
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Running Dall-e mini on Windows? (Or: Are there any equivalent text-to-image AI's I can run on a windows PC with a 2080 TI?)
Another option is https://github.com/jina-ai/dalle-flow combines DALL-E Mini with some other image processing models, and they have a pre-built Docker image that you could run locally. However, because it loads additional image processing models, you'll need about 21 GB of GPU RAM which is more than a 2080 TI has. You could always try to edit their Dockerfile and re-build it to remove the other models.
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Run Your Own DALLĀ·E Mini (Craiyon) Server on EC2
For the second half of this article, weāll use meadowdata/meadowrun-dallemini-demo which contains a notebook for running multiple models as sequential batch jobs to generate images using Meadowrun. The combination of models is inspired by jina-ai/dalle-flow.
What are some alternatives?
dalle-mini - DALLĀ·E Mini - Generate images from a text prompt
Dannjs - Easy to use Deep Neural Network Library for JavaScript.
jina - āļø Build multimodal AI applications with cloud-native stack
CogVideo - Text-to-video generation. The repo for ICLR2023 paper "CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers"
BasicSR - Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, BasicVSR, SwinIR, ECBSR, etc. Also support StyleGAN2, DFDNet.
min-dalle - min(DALLĀ·E) is a fast, minimal port of DALLĀ·E Mini to PyTorch
example-app-store - App store search example, using Jina as backend and Streamlit as frontend
nano-neuron - š¤ NanoNeuron is 7 simple JavaScript functions that will give you a feeling of how machines can actually "learn"
dalle2-in-python - Use DALLĀ·E 2 in Python
pollinations - Generate Art
argilla - Argilla is a collaboration platform for AI engineers and domain experts that require high-quality outputs, full data ownership, and overall efficiency.