transfer-learning-conv-ai
BigGAN-PyTorch
| transfer-learning-conv-ai | BigGAN-PyTorch | |
|---|---|---|
| 3 | 4 | |
| 1,711 | 2,804 | |
| 0.0% | - | |
| 0.0 | 0.0 | |
| 11 months ago | 10 months ago | |
| Python | Python | |
| MIT License | MIT License |
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.
transfer-learning-conv-ai
- will gpt2 run in my laptop
-
[D] [R] Dialogue generation with contrastive objectives
Code for https://arxiv.org/abs/1901.08149 found: https://github.com/huggingface/transfer-learning-conv-ai
-
Messing around with an AI
https://github.com/huggingface/transfer-learning-conv-ai (Requires an hefty GPU though...)
BigGAN-PyTorch
-
[D] Pre-trained weights for GANs online?
The second link gives you the entire source code for training the model https://github.com/ajbrock/BigGAN-PyTorch/tree/master . Looks like BigGAN.py and BigGANdeep.py are the two files that define the architecture. Can you work with that?
-
I'm looking for an AI Art generator from images
BigGAN (https://github.com/ajbrock/BigGAN-PyTorch) - This is a PyTorch implementation of the BigGAN model for generating high-resolution images. It is trained on a large dataset and can generate a wide range of images, including photographs of animals, objects, and landscapes.
-
[D] Using activity regularization instead of batch norm.
Tangentially, theoretically you can't use BN in the discriminator for WGAN-GP anyway (assuming that you're using the Gulrajani work) because it breaks the sample independence assumptions of the GP. If you have a relatively structured dataset (eg all faces, all cars, all giraffes, etc.) and no class conditioning, look into StyleGAN2-ADA for the best results. If you have a dataset with a lot of variation and a lot of classes try using the BigGAN repo.
-
Έφτιαξα ένα AI που παράγει εικόνες από μερικές λέξεις. Να τι έφτιαξε όταν του είπα να σκεφτεί ένα "Αφηρημένο Πορτρέτο"
BigGan και Deep Dream https://github.com/ajbrock/BigGAN-PyTorch https://github.com/google/deepdream
What are some alternatives?
haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
stylegan2-ada-pytorch - StyleGAN2-ADA - Official PyTorch implementation
GPT2-Chinese - Chinese version of GPT2 training code, using BERT tokenizer.
pytorch-tutorial - PyTorch Tutorial for Deep Learning Researchers
DeepFake-Detection - Towards deepfake detection that actually works
PyTorch-StudioGAN - StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
sense - Enhance your application with the ability to see and interact with humans using any RGB camera.
pytorch-forecasting - Time series forecasting with PyTorch
DialogRPT - EMNLP 2020: "Dialogue Response Ranking Training with Large-Scale Human Feedback Data"
code-generator - Web Application to generate your training scripts with PyTorch Ignite
Code-LMs - Guide to using pre-trained large language models of source code
pytorch-CycleGAN-and-pix2pix - Image-to-Image Translation in PyTorch