text-to-text-transfer-transformer
DALLE2-pytorch
text-to-text-transfer-transformer | DALLE2-pytorch | |
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29 | 65 | |
5,909 | 10,826 | |
1.1% | - | |
5.0 | 6.8 | |
3 months ago | 3 months ago | |
Python | Python | |
Apache License 2.0 | MIT License |
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text-to-text-transfer-transformer
- T5: Text-to-Text-Transfer-Transformer
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Gemma: New Open Models
Google released the T5 paper about 5 years ago:
https://arxiv.org/abs/1910.10683
This included full model weights along with a detailed description of the dataset, training process, and ablations that led them to that architecture. T5 was state-of-the-art on many benchmarks when it was released, but it was of course quickly eclipsed by GPT-3.
Following GPT-3, it became much more common for labs to not release full details or model weights. Prior to that, it was common practice from Google (BERT, T5), Meta (BART), OpenAI (GPT1, GPT2) and others to release full training details and model weights.
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[P] Free and Fast LLM Finetuning
[2] - https://arxiv.org/abs/1910.10683
- Free and Fast LLM Finetuning
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[Discussion] Is there a better way than positional encodings in self attention?
T5-style relative encodings https://arxiv.org/abs/1910.10683
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What were the 40 research papers on the list Ilya Sutskever gave John Carmack?
11. T5: Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer" (2020) - https://arxiv.org/abs/1910.10683 (Google Research)
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[P] T5 Implementation in PyTorch
You can find a link to the paper here: https://arxiv.org/abs/1910.10683
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Text-to-Text Transformer (T5-Base Model) Testing For Summarization, Sentiment Classification, and Translation Using Pytorch and Torchtext
The Text-to-Text Transformer is a type of neural network architecture that is particularly well-suited for natural language processing tasks involving the generation of text. It was introduced in the paper "Attention is All You Need" by Vaswani et al. and has since become a popular choice for many NLP tasks, including language translation, summarization, and text generation
- AlphaCode by DeepMind
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[R] LiBai: a large-scale open-source model training toolbox
Found relevant code at https://github.com/google-research/text-to-text-transfer-transformer + all code implementations here
DALLE2-pytorch
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One year ago I got access to closed beta DALL-E 2.
I was showing people Dalle2 last year and telling them how much of an impact an open source solution was going to have on, well, everything to do with art and design. (At the time Stable Diffusion had not released, not even the leak, and all hopes was on https://github.com/lucidrains/DALLE2-pytorch)
- [Machinelearning] [D] Quelqu'un travaille-t-il sur l'open-sourcing de Dall-E 2 ?
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AMA (Emad here hello)
Stable diffusion is the model, MJ will use a variant and DALL-E is the old version (we have our own implementation from our distinguished fellow Lucidrains here: https://github.com/lucidrains/DALLE2-pytorch)
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An impressionist painting of an floating raccoon god, 4k, digital painting, trending on artstation
Sadly I don't think so. From what I understand the architecture is fixed to 1024x1024 pictures.
- I asked AI to turn P&R characters into muppets..
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Comparison of AI text-to-image generators
The code is open source, the model is not I believe. https://github.com/lucidrains/DALLE2-pytorch
- Protests erupt outside of DALL-E offices after pricing implementation, press photograph
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$15 for 115 “generation increments” Very expensive Beta pricing announcement. Dissapointed
Phil Wang has been fairly prolific at creating open source implementations of these text to image models. For example, here is the dalle-2 repo https://github.com/lucidrains/DALLE2-pytorch
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DALL·E Now Available in Beta
There's already an open-source implementation of DALL-E 2 (https://github.com/lucidrains/DALLE2-pytorch) and a pretrained model for it should be released within this year.
Also true for Google's Imagen, which should be even better than DALLE-2 (and faster) https://github.com/lucidrains/imagen-pytorch.
This is possible because the original research papers behind both DALLE-2 and Imagen were publicly released.
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would love to know what portion of this prompt is not allowed
The paper describing the model is public and has been implemented here, but that's not the hard part. The model likely requires months of compute and dozens of gigabytes of VRAM to train and run, likely costing several hundred thousand dollars.
What are some alternatives?
fairseq - Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
dalle-mini - DALL·E Mini - Generate images from a text prompt
tortoise-tts - A multi-voice TTS system trained with an emphasis on quality
disco-diffusion
DeepCreamPy - Decensoring Hentai with Deep Neural Networks
DALLE-pytorch - Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
DALL-E - PyTorch package for the discrete VAE used for DALL·E.
latent-diffusion - High-Resolution Image Synthesis with Latent Diffusion Models
dalle-2-preview
majesty-diffusion - Majesty Diffusion by @Dango233(@Dango233max) and @apolinario (@multimodalart)