MiniGPT-4
stable-diffusion-webui-wd14-tagger
MiniGPT-4 | stable-diffusion-webui-wd14-tagger | |
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37 | 15 | |
24,899 | 888 | |
0.8% | - | |
9.1 | 8.6 | |
12 days ago | 10 months ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | - |
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MiniGPT-4
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"Building Machines That Learn and Think Like People", 7 Years Later
I just think the tech has been out for so long it's not as big of a deal. Mini-Gpt4 has been out for 6 months! Of course the descriptions aren't exactly gpt-4 grade, but with mistral 7b being used as the language model instead of llama 7b, the reasoning ability will improve noticeably.
[1] https://github.com/Vision-CAIR/MiniGPT-4
- Minigpt4 Inference on CPU
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Multimodal LLM for infographics images
Isn't there only two open multimodal LLMs, LLaVA and mini-gpt4?
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Ai trained on photos
For LLM visual instruction, you can use LLaVA, LaVIN, or MiniGPT-4.
- CLIP and DeepDanbooru Alternatives For Prompt Generation [Relevant Self-Promotion]
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Looking for a pre trained food recognition model
Please read the rules before posting. If you want a model for visual instruction, use LLaVA, LaVIN, or MiniGPT-4.
- Minigpt-4 (Vicuna 13B + images)
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Upload a photo of your meal and get roasted by ChatGPT
So we use MiniGPT-4 for image parsing, and yep it does return a pretty detailed (albeit not always accurate) description of the photo. You can actually play around with it on Huggingface here.
We use MiniGPT-4 first to interpret the image and then pass the results onto GPT-4. Hopefully, once GPT-4 makes its multi-modal functionality available, we can do it all in one request.
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Give some love to multi modal models trained on censored llama based models
But I would like to bring up that there are some multi models(llava, miniGPT-4) that are built based on censored llama based models like vicuna. I tried several multi modal models like llava, minigpt4 and blip2. Llava has very good captioning and question answering abilities and it is also much faster than the others(basically real time), though it has some hallucination issue.
stable-diffusion-webui-wd14-tagger
- CLIP and DeepDanbooru Alternatives For Prompt Generation [Relevant Self-Promotion]
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Ideas for extensions?
Create an extension like 'send pictures' that uses the WD14 tagger which is way more detailed and has options for nsfw etc. Its used in Automatic1111 and Koyha ss so there's extensions you can probably implement from. https://github.com/toriato/stable-diffusion-webui-wd14-tagger
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vladmandic-WD14-Tagger
If anyone is interested I made some changes to toriato's wd14-tagger, now it works also on vladmandic webui, repo here. You can do a new installation, or use your old automatic1111 one changing 3 files, instructions on my repo. The lora files also work (there were some problems in the vlad issue page). I'm not a programmer and it's not perfect though, in fact for now if you don't like the default tagger model you have to change it manually (instructions in the repo), and since it is basically a fork of toriato's version, if there were errors there, there will be here too.
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Community-trained SD 1.6 Model, can we do it?
Automatic captioning tools that can be used as an initial point for captions: this tool or this one.
- Is anyone able to make the tagger extension compatible with Vlad UI ?
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What are your favorite Extensions?
wd14-tagger, to describe anime images and get a prompt idea
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Experiment AI Anime w/ C-Net 1.1 + GroundingDINO + SAM + MFR (workflow)
Use WD 1.4 tagger (https://github.com/toriato/stable-diffusion-webui-wd14-tagger) to extract prompt words from each frame (threshold 0.65), then use the dataset tag editor (https://github.com/toshiaki1729/stable-diffusion-webui-dataset-tag-editor) for batch editing, mainly:
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Currently getting better results with Kohya ss Loras (Lycoris Locon) than with DB, am I alone?
I recommend using EveryDream2. You'll need an 11GB VRAM GPU. There's no need to crop or resize images, just caption them, which can be done automatically with CLIP Interrogator or WD14 taggers. Make sure to add the trigger word for your subject. It's not a Dreambooth script; it's actual training, so it shouldn't be as destructive to the model as Dreambooth. Typically, using an LR of 1e-6 with a cosine scheduler over two epochs and a batch size of 4 works fine. This script supports validation, so you can actually watch in real-time whether the training is going well or if you're overfitting. I got very good results using it.
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For Lora training, isn’t there a good AI that discribes the pictures you want to use for training?
In my current process, I use CLIP Interrogator to produce a high level caption and wd14 tagger for more granular booru tags. Typically in that order, because you can append the results from the latter to the former. Both tools perform with greater accuracy than the standard interrogators in img2img and give you more flexibility and features as well. You still have to do some manual adjustments, but I generally prefer this process over starting from scratch.
- Captioning LoRA's
What are some alternatives?
LLaVA - [NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
clip-interrogator - Image to prompt with BLIP and CLIP
FastChat - An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.
batch-face-swap - Automaticaly detects faces and replaces them
AutoGPT - AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
sd_dreambooth_extension
BooruDatasetTagManager
stable-diffusion-webui - Stable Diffusion web UI
bark - 🔊 Text-Prompted Generative Audio Model
automatic - SD.Next: Advanced Implementation of Stable Diffusion and other Diffusion-based generative image models
mini-agi - MiniAGI is a simple general-purpose autonomous agent based on the OpenAI API.
stable-diffusion-webui-dataset-tag-editor - Extension to edit dataset captions for SD web UI by AUTOMATIC1111