dalle-2-preview VS glide-text2im

Compare dalle-2-preview vs glide-text2im and see what are their differences.

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dalle-2-preview glide-text2im
61 32
1,044 3,580
0.0% 0.4%
1.8 0.0
over 2 years ago 12 months ago
Python
- MIT License
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.
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.

dalle-2-preview

Posts with mentions or reviews of dalle-2-preview. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-08-16.

glide-text2im

Posts with mentions or reviews of glide-text2im. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-14.

What are some alternatives?

When comparing dalle-2-preview and glide-text2im you can also consider the following projects:

dalle-mini - DALL·E Mini - Generate images from a text prompt

glide-text2im-colab - Colab notebook for openai/glide-text2im.

DALL-E - PyTorch package for the discrete VAE used for DALL·E.

v-diffusion-pytorch - v objective diffusion inference code for PyTorch.

latent-diffusion - High-Resolution Image Synthesis with Latent Diffusion Models

pixray

CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

lm-human-preferences - Code for the paper Fine-Tuning Language Models from Human Preferences

clip-interrogator - Image to prompt with BLIP and CLIP

glid-3-xl - 1.4B latent diffusion model fine tuning

disco-diffusion

improved-diffusion - Release for Improved Denoising Diffusion Probabilistic Models

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Other PDF SDKs promise a lot - then break. Laggy scrolling, poor mobile UX, tons of bugs, and lack of support cost you endless frustrations. Nutrient’s SDK handles billion-page workloads - so you don’t have to debug PDFs. Used by ~1 billion end users in more than 150 different countries.
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