textual_inversion
VideoX
textual_inversion | VideoX | |
---|---|---|
30 | 7 | |
2,743 | 932 | |
- | 1.3% | |
0.8 | 3.9 | |
about 1 year ago | about 1 month ago | |
Jupyter Notebook | Python | |
MIT License | GNU General Public License v3.0 or later |
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textual_inversion
- FLiP Stack Weekly for 06 February 2023
- Loading textual inversion embeddings in vanilla SD library?
- Embeddings without using AUTO1111
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How to use embeddings with PyTorch
Checking out https://github.com/rinongal/textual_inversion, which has some possibly informative examples and scripts.
- Textual Inversion
- Advice on Automatic1111 textual inversion tuning?
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Hi. Is training my own textual inversion feasible on one 1070? &how long does it take?
I think currently you will need about 20GB VRam..., options are: 1. https://github.com/rinongal/textual_inversion - localy
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Question About Running Local Textual Inversion
Rinongal and nicolai256 versions, the latter of which is also the one explained in Nerdy Rodent's youtube video https://www.youtube.com/watch?v=WsDykBTjo20, work but they also have an issue of lacking editability in comparison to one made by huggingface's collab which is followed up in a very long issue on Rinongal's Github. You can add accumulate_grad_batches: 4 to the end of the finetune files like shown in Nerdy Rodent's video at this time stamp to try to alleviate this issue, but the quality isn't as good as one made in the online collab.
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How close are we to full movie generation from a technical standpoint?
That may mostly solve that but it’s too early right now: https://github.com/rinongal/textual_inversion
For fun I tried to make an entire animated music video but it took over one week of processing and basically fell apart coherently by 30 seconds so just did one third:
https://youtu.be/f3GfUKJBUYA
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Easy Textual Inversion tutorial. How To Train Stable Diffusion With Your Own Art.
The huggingface models don't work with the local stable diffusion, only the models trained locally with this repo https://github.com/rinongal/textual_inversion can be installed, at least for now.
VideoX
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Generative AI
Input Output Theme Use Case Example Platforms Text Text Marketing Copywriting, creative personalisation, SEO optimisation Jasper AI (https://www.jasper.ai/) WRITER (https://writer.com/) Video Video / Text Sales Business development agumentation, Sales coaching https://www.regie.ai/ https://www.oliv.a/ Audio Text / Audio CRM Customer service chatbots (answering tickets and queries) https://symbl.ai/ https://forethought.ai/ Audio / Text Audio / Text Talent Management Performance management, Job interviews, Coaching, training https://www.onloop.com/ https://www.converzai.com/ Text Text Legal Contract drafting, Legal validation / citations https://casetext.com/ Text Text Code creation Natural language to generate code for softwares. AI pair programmer https://mayalabs.io/ https://github.com/features/copilot https://debuild.app/ https://kombai.io/ Text Text Code Documentation Natural language to generate code for softwares. AI pair programmer https://mayalabs.io/ https://github.com/features/copilot Text Image Art Generation AI system that can create realistic images and art from a description in natural language. https://openai.com/dall-e-2/ https://midjourney.com/home/?callbackUrl=%2Fapp%2F Text Text ML Model Build, train and deploy AI models https://huggingface.co/ https://replicate.com/ Text Audio Voice Synthesis Educational platform, training, Cognitive coaching https://synthesys.io/ https://speechify.com/ Text Video Video Educational platform, training, Cognitive coaching https://www.synthesia.io/ https://github.com/microsoft/VideoX/tree/master/X-CLIP Text Image 3D modelling Storyboarding for games, 3D video modelling https://nv-tlabs.github.io/GET3D/ https://dreamfusion3d.github.io/
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General Video Recognition with AI (How AI Understands Videos)
►Code: https://github.com/microsoft/VideoX/tree/master/X-CLIP
- [D] Most Popular AI Research Aug 2022 - Ranked Based On GitHub Stars
- Most Popular AI Research Aug 2022 pt. 2 - Ranked Based On GitHub Stars
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Stable Diffusion: Is Video Coming Soon?
The pieces are coming into place https://github.com/microsoft/VideoX/tree/master/X-CLIP
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Latest Computer Vision Research At Microsoft Explains How This Proposed Method Adapts The Pretrained Language Image Models To Video Recognition
Continue reading | Check out the paper and github link
What are some alternatives?
stable-diffusion - A latent text-to-image diffusion model
bitsandbytes - Accessible large language models via k-bit quantization for PyTorch.
Intrusion-Detection-System-Using-Machine-Learning - Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)
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.
frame-interpolation - FILM: Frame Interpolation for Large Motion, In ECCV 2022.
stable-diffusion-webui - Stable Diffusion web UI
Awesome-Dataset-Distillation - Awesome Dataset Distillation Papers
stable-diffusion - This version of CompVis/stable-diffusion features an interactive command-line script that combines text2img and img2img functionality in a "dream bot" style interface, a WebGUI, and multiple features and other enhancements. [Moved to: https://github.com/invoke-ai/InvokeAI]
PeRFception - [NeurIPS2022] Official implementation of PeRFception: Perception using Radiance Fields.
Stable-textual-inversion_win
MinVIS