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Detailed Comparison of JoyCaption Alpha One vs JoyCaption Pre-Alpha — 10 Different Style Amazing Images — I think JoyCaption Alpha One is the very best image captioning model at the moment for model training — Works very fast and requires as low as 8.5 GB VRAM
Where To Download And Install
You can download our APP from here : https://www.patreon.com/posts/110613301
1-Click to install on Windows, RunPod and Massed Compute
Official APP is here where you can try : fancyfeast/joy-caption-alpha-one
Have The Following Features
Auto downloads meta-llama/Meta-Llama-3.1–8B into your Hugging Face cache folder and other necessary models into the installation folder
Use 4-bit quantization — Uses 8.5 GB VRAM Total
Overwrite existing caption file
Append new caption to existing caption
Remove newlines from generated captions
Cut off at last complete sentence
Discard repeating sentences
Don’t save processed image
Caption Prefix
Caption Suffix
Custom System Prompt (Optional)
Input Folder for Batch Processing
Output Folder for Batch Processing (Optional)
Fully supported Multi GPU captioning — GPU IDs (comma-separated, e.g., 0,1,2)
Batch Size — Batch captioning
Where To Download And Install
You can download our APP from here : https://www.patreon.com/posts/110613301
1-Click to install on Windows, RunPod and Massed Compute
Official APP is here where you can try : fancyfeast/joy-caption-alpha-one
Have The Following Features
Auto downloads meta-llama/Meta-Llama-3.1–8B into your Hugging Face cache folder and other necessary models into the installation folder
Use 4-bit quantization — Uses 8.5 GB VRAM Total
Overwrite existing caption file
Append new caption to existing caption
Remove newlines from generated captions
Cut off at last complete sentence
Discard repeating sentences
Don’t save processed image
Caption Prefix
Caption Suffix
Custom System Prompt (Optional)
Input Folder for Batch Processing
Output Folder for Batch Processing (Optional)
Fully supported Multi GPU captioning — GPU IDs (comma-separated, e.g., 0,1,2)
Batch Size — Batch captioning
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