Instructions to use sayakpaul/instruct-pix2pix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sayakpaul/instruct-pix2pix with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("sayakpaul/instruct-pix2pix", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Update model_index.json
#1
by tolgacangoz - opened
- model_index.json +3 -2
model_index.json
CHANGED
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@@ -1,9 +1,10 @@
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{
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"_class_name": "StableDiffusionInstructPix2PixPipeline",
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"_diffusers_version": "0.
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"feature_extractor": [
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"transformers",
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"
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],
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"requires_safety_checker": true,
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"safety_checker": [
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{
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"_class_name": "StableDiffusionInstructPix2PixPipeline",
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"_diffusers_version": "0.21.4",
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"_name_or_path": "sayakpaul/instruct-pix2pix",
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"feature_extractor": [
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"transformers",
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"CLIPImageProcessor"
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],
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"requires_safety_checker": true,
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"safety_checker": [
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