TensorFlow2.0_Notebooks VS ai-art-generator

Compare TensorFlow2.0_Notebooks vs ai-art-generator and see what are their differences.

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TensorFlow2.0_Notebooks ai-art-generator
1 3
37 627
- -
0.0 0.0
about 3 years ago about 1 year ago
Jupyter Notebook Python
MIT License GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.

TensorFlow2.0_Notebooks

Posts with mentions or reviews of TensorFlow2.0_Notebooks. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-04-17.

ai-art-generator

Posts with mentions or reviews of ai-art-generator. We have used some of these posts to build our list of alternatives and similar projects.
  • Cheap setup to run SD?
    1 project | /r/StableDiffusion | 5 Sep 2022
    I have a github project that will help you set up large batches of prompts too.
  • Local AI art generation tool updated for Stable Diffusion
    1 project | /r/bigsleep | 22 Aug 2022
    Hey all, just a note that I've updated my AI-art generator to work with Stable Diffusion (both txt2img and imgtoimg)! If you have a decent GPU (8GB VRAM+, though more is better), you should be able to use Stable Diffusion on your local computer.
  • Tesla M40 24GB GPU: very poor machine-learning performance?
    1 project | /r/MLQuestions | 1 Jan 2022
    I'm a software engineer, but a complete machine-learning noob (not exactly a linux guru, either). I'm trying to use the GPU for VQGAN+CLIP image generation. Running on an RTX 3060, I get almost 4 iterations per second, so a 512x512 image takes about 2 minutes to create with default settings. Running on the Tesla M40, I get about 0.4 iterations per second (~22 minutes per 512x512 image at the same settings). A full order of magnitude slower! I'd read that older Tesla GPUs are some of the top value picks when it comes to ML applications, but obviously with this level of performance that isn't the case at all. I figure I must be going wrong somewhere.

What are some alternatives?

When comparing TensorFlow2.0_Notebooks and ai-art-generator you can also consider the following projects:

mmcv - OpenMMLab Computer Vision Foundation

vqgan-clip-generator - Implements VQGAN+CLIP for image and video generation, and style transfers, based on text and image prompts. Emphasis on ease-of-use, documentation, and smooth video creation.

Time-Series-Forecasting-Using-LSTM - Time-Series Forecasting on Stock Prices using LSTM

Animender - An AI that recommends anime based on personal history.

cryptocurrency-price-prediction - Cryptocurrency Price Prediction Using LSTM neural network

tensorflow-deep-learning - All course materials for the Zero to Mastery Deep Learning with TensorFlow course.

strv-ml-mask2face - Virtually remove a face mask to see what a person looks like underneath

Deep-Learning-With-TensorFlow - All the resources and hands-on exercises for you to get started with Deep Learning in TensorFlow

TensorFlow-Tutorials - TensorFlow Tutorials with YouTube Videos

ReVersion - ReVersion: Diffusion-Based Relation Inversion from Images

Deep-Learning-In-Production - Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.

TTS - πŸΈπŸ’¬ - a deep learning toolkit for Text-to-Speech, battle-tested in research and production