Spaces:
Running
on
Zero
Running
on
Zero
fancyfeast
commited on
Commit
·
27c9477
1
Parent(s):
89e9fac
Update version and tweak the UI
Browse files- README.md +1 -1
- app.py +5 -3
- requirements.txt +1 -2
README.md
CHANGED
@@ -4,7 +4,7 @@ emoji: 🖼️💬
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colorFrom: yellow
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colorTo: blue
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sdk: gradio
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sdk_version: 5.
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app_file: app.py
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pinned: false
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---
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colorFrom: yellow
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colorTo: blue
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sdk: gradio
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sdk_version: 5.29.0
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app_file: app.py
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pinned: false
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---
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app.py
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@@ -8,11 +8,10 @@ from typing import Generator
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MODEL_PATH = "fancyfeast/llama-joycaption-beta-one-hf-llava"
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TITLE = "<h1><center>JoyCaption Beta One - (2025-05-10a)</center></h1>"
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DESCRIPTION = """
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<div>
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<p></p>
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<p>**This model cannot see any chat history.**</p>
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<p>🚨🚨🚨 If the "Help improve JoyCaption" box is checked, the _text_ query you write will be logged and I _might_ use it to help improve JoyCaption.
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It does not log images, user data, etc; only the text query. I cannot see what images you send, and frankly, I don't want to. But knowing what kinds of instructions
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and queries users want JoyCaption to handle will help guide me in building JoyCaption's dataset. This dataset will be made public. As always, the model itself is completely
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"Write a descriptive caption for this image in a casual tone within {word_count} words.",
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"Write a {length} descriptive caption for this image in a casual tone.",
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],
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"
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"Write a stable diffusion prompt for this image.",
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"Write a stable diffusion prompt for this image within {word_count} words.",
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"Write a {length} stable diffusion prompt for this image.",
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@@ -238,6 +237,9 @@ with gr.Blocks() as demo:
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outputs=output_caption,
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)
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gr.Markdown(DESCRIPTION)
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MODEL_PATH = "fancyfeast/llama-joycaption-beta-one-hf-llava"
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TITLE = "<h1><center>JoyCaption Beta One - (2025-05-10a)</center></h1>JoyCaption is an image captioning model"
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DESCRIPTION = """
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<div>
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<p></p>
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<p>🚨🚨🚨 If the "Help improve JoyCaption" box is checked, the _text_ query you write will be logged and I _might_ use it to help improve JoyCaption.
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It does not log images, user data, etc; only the text query. I cannot see what images you send, and frankly, I don't want to. But knowing what kinds of instructions
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and queries users want JoyCaption to handle will help guide me in building JoyCaption's dataset. This dataset will be made public. As always, the model itself is completely
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"Write a descriptive caption for this image in a casual tone within {word_count} words.",
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"Write a {length} descriptive caption for this image in a casual tone.",
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],
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"Stable Diffusion Prompt": [
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"Write a stable diffusion prompt for this image.",
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"Write a stable diffusion prompt for this image within {word_count} words.",
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"Write a {length} stable diffusion prompt for this image.",
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outputs=output_caption,
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)
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# Initial prompt
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prompt_box.value = build_prompt(caption_type.value, caption_length.value, extra_options.value, name_input.value)
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gr.Markdown(DESCRIPTION)
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requirements.txt
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@@ -3,5 +3,4 @@ accelerate
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torch
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transformers==4.51.0
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sentencepiece
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torchvision
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pydantic==2.10.6
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torch
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transformers==4.51.0
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sentencepiece
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torchvision
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