KoboldAI
stable-diffusion-webui
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KoboldAI | stable-diffusion-webui | |
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41 | 2,808 | |
327 | 129,975 | |
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9.5 | 9.9 | |
14 days ago | 1 day ago | |
C++ | Python | |
GNU Affero General Public License v3.0 | MIT |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
KoboldAI
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LLM spews nonsense in CVE report for curl
It’s not that big a task as all that. There are a lot of unaligned models available, and user interfaces that aren’t that hard to use.
https://github.com/henk717/KoboldAI
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Chat with, and help host, a free community LLM "horde"
https://github.com/henk717/KoboldAI
- Hosts pick a quantized community LLM to run, which is (IMO) the real magic of this system. Cloud services tend to run generic Llama chat/instruct models, OpenAI API models, or maybe a single proprietary finetune, but the Llama/Mistral finetuning community is red hot. New finetines and crazy merges/hybrids that outperform llama-chat in specific tasks (mostly Chat/Story/RP) come out every day, and each one has a different "flavor" and format:
https://huggingface.co/models?sort=modified&search=mistral+g...
- Run LLMs with KoboldaAI on Intel ARC
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No idea what I'm doing help
Sourceforge is our official version but that one is to old to run newer models like Holomax, the releases for United can be found here : https://github.com/henk717/KoboldAI/releases
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Still getting "read only" on JanitorAI even after setting model. Do I need to change anything config wise to get it to use pygmalion?
Colab Check: False, TPU: False INIT | OK | KAI Horde Models INFO | __main__::648 - We loaded the following model backends: KoboldAI API KoboldAI Old Colab Method Huggingface GooseAI Horde OpenAI Read Only INFO | __main__:general_startup:1363 - Running on Repo: https://github.com/henk717/koboldai Branch: INIT | Starting | Flask INIT | OK | Flask INIT | Starting | Webserver INIT | OK | Webserver MESSAGE | Webserver started! You may now connect with a browser at http://127.0.0.1:8501 INIT | Searching | GPU support INIT | Found | GPU support INIT | Starting | LUA bridge INIT | OK | LUA bridge INIT | Starting | LUA Scripts INIT | OK | LUA Scripts Setting Seed Traceback (most recent call last): File "B:\python\lib\site-packages\eventlet\hubs\selects.py", line 59, in wait listeners.get(fileno, hub.noop).cb(fileno) File "B:\python\lib\site-packages\eventlet\greenthread.py", line 221, in main result = function(*args, **kwargs) File "B:\python\lib\site-packages\eventlet\wsgi.py", line 837, in process_request proto.__init__(conn_state, self) File "B:\python\lib\site-packages\eventlet\wsgi.py", line 352, in __init__ self.finish() File "B:\python\lib\site-packages\eventlet\wsgi.py", line 751, in finish BaseHTTPServer.BaseHTTPRequestHandler.finish(self) File "B:\python\lib\socketserver.py", line 811, in finish self.wfile.close() File "B:\python\lib\socket.py", line 687, in write return self._sock.send(b) File "B:\python\lib\site-packages\eventlet\greenio\base.py", line 401, in send return self._send_loop(self.fd.send, data, flags) File "B:\python\lib\site-packages\eventlet\greenio\base.py", line 388, in _send_loop return send_method(data, *args) ConnectionAbortedError: [WinError 10053] An established connection was aborted by the software in your host machine Removing descriptor: 1488 Connection Attempt: 127.0.0.1 INFO | __main__:do_connect:2574 - Client connected! UI_1 TODO: Allow config INFO | modeling.inference_models.hf:set_input_parameters:189 - {'0_Layers': 18, 'CPU_Layers': 10, 'Disk_Layers': 0, 'class': 'model', 'label': 'PygmalionAI_pygmalion-6b', 'id': 'PygmalionAI_pygmalion-6b', 'name': 'PygmalionAI_pygmalion-6b', 'size': '', 'menu': 'Custom', 'path': 'C:\\KoboldAI\\models\\PygmalionAI_pygmalion-6b', 'ismenu': 'false', 'plugin': 'Huggingface'} INIT | Searching | GPU support INIT | Found | GPU support Loading checkpoint shards: 100%|█████████████████████████████████████████████████████████| 2/2 [00:19<00:00, 9.60s/it] Loading model tensors: 100%|##########| 56/56 [00:05<00:00, 9.52it/s]INIT | Starting | LUA bridge0, 8.93s/it] INIT | OK | LUA bridge INIT | Starting | LUA Scripts INIT | OK | LUA Scripts Setting Seed Connection Attempt: 127.0.0.1 INFO | __main__:do_connect:2574 - Client connected! UI_1
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Kobold API URL for Chub Venus Ai
That is our developer version, its selectable in the Colab version dropdown and also available on https://github.com/henk717/koboldai
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I got KoboldAI running on my computer and successfully connected it to Janitor, heres a small tutorial
Download Kobold from THIS LINK:https://github.com/henk717/KoboldAI. I downloaded Kobold from a different Github link and it wouldnt work, you need to get this specific one. Click on "code", then download zip
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I created a repo on Github to categorize AI models. You can browse AIs from many categories!
https://github.com/henk717/KoboldAI https://github.com/LostRuins/koboldcpp/ https://github.com/ggerganov/llama.cpp https://github.com/AUTOMATIC1111/stable-diffusion-webui https://github.com/oobabooga/text-generation-webui
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Meta’s new AI lets people make chatbots. They’re using it for sex.
For the third, I don't think Oobabooga supports the horde but KoboldAI does. I won't go into how to install KoboldAI since Oobabooga should give you enough freedom with 7B, 13B and maybe 30B models (depending on available RAM), but KoboldAI lets you download some models directly from the web interface, supports using online service providers to run the models for you, and supports the horde with a list of available models to choose from.
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Kobold AI broke after update (New to this)
"Your Pytorch installation did not update correctly, you can solve this by running install_requirements.bat in the mode where it deletes the existing runtime. Alternative you can download a fresh copy of the offline installer for KoboldAI United from : https://github.com/henk717/KoboldAI/releases"
stable-diffusion-webui
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Show HN: I made an app to use local AI as daily driver
* LLaVA model: I'll add more documentation. You are right Llava could not generate images. For image generation I don't have immediate plans, but checkout these projects for local image generation.
- https://diffusionbee.com/
- https://github.com/comfyanonymous/ComfyUI
- https://github.com/AUTOMATIC1111/stable-diffusion-webui
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AMD Funded a Drop-In CUDA Implementation Built on ROCm: It's Open-Source
I would love to be able to have a native stable diffusion experience, my rx 580 takes 30s to generate a single image. But it does work after following https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki...
I got this up and running on my windows machine in short order and I don't even know what stable diffusion is.
But again, it would be nice to have first class support to locally participate in the fun.
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Ask HN: What is the state of the art in AI photo enhancement?
In Auto1111, that just uses Image.blend. :)
https://github.com/AUTOMATIC1111/stable-diffusion-webui/blob...
- How To Increase Performance Time on MacOS
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Can anyone suggest an AI model that can help me enhance a poorly drawn logo?
I used SDXL in automatic1111 webui for both images. Now that I think about it, the procedure I described was how I made this one, but the one that looks like an illustration was done in two steps. I used the canny ControlNet as I said for the outer part of the logo to preserve the shape of the fonts, but I had to turn it off for the boot to give SDXL leeway to add detail and make it look more like a boot.
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Seeking out an experienced and empathetic coding buddy.
That said, please do learn coding and don't get discouraged when somebody says to learn PyTorch or recommends using a Jupiter notebook with no further information on how to translate the skill into images. I would highly recommend some short term goals. Get your feet wet by taking apart the UIs. The comfy API documentation is here and the A1111 API documentation is here. There is a difference in completeness, welcome to programming. Writing nodes or plugins is also a good way to jump into this world. Custom wildcard logic might be very attractive to you if you aren't the type that want to deal with a nested file structure to simulate logic.
- can't get it working with an AMD gpu
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SD extension that allows for setting override
Possibly Unprompted? https://github.com/AUTOMATIC1111/stable-diffusion-webui/discussions/8094
- Need to write an application to use Stable Diffusion on my desktop PC - which resource should I learn to use?
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4090 Speed Decrease on each Generation/Iteration
version: v1.6.1 • python: 3.10.13 • torch: 2.0.1+cu118 • xformers: 0.0.20 • gradio: 3.41.2 • checkpoint: 6e8d4871f8
What are some alternatives?
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
stable-diffusion-ui - Easiest 1-click way to install and use Stable Diffusion on your computer. Provides a browser UI for generating images from text prompts and images. Just enter your text prompt, and see the generated image. [Moved to: https://github.com/easydiffusion/easydiffusion]
KoboldAI-Client
ComfyUI - The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
koboldcpp - A simple one-file way to run various GGML and GGUF models with KoboldAI's UI
SHARK - SHARK - High Performance Machine Learning Distribution
KoboldAI
lora - Using Low-rank adaptation to quickly fine-tune diffusion models.
llama.cpp - LLM inference in C/C++
InvokeAI - InvokeAI is a leading creative engine for Stable Diffusion models, empowering professionals, artists, and enthusiasts to generate and create visual media using the latest AI-driven technologies. The solution offers an industry leading WebUI, supports terminal use through a CLI, and serves as the foundation for multiple commercial products.
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
safetensors - Simple, safe way to store and distribute tensors