Instructions to use jcplus/waifu-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jcplus/waifu-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jcplus/waifu-diffusion", 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
- Local Apps
- Draw Things
- DiffusionBee
Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`.
Browse filesHey jcplus 👋,
Your model repository seems to contain logic to load a feature extractor that is deprecated, which you should notice by seeing the warning:
```
transformers/models/clip/feature_extraction_clip.py:28: FutureWarning: The class CLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please use CLIPImageProcessor instead. warnings.warn(
```
when running `pipe = DiffusionPipeline.from_pretrained(jcplus/waifu-diffusion)`.This PR makes sure that the warning does not show anymore by replacing `CLIPFeatureExtractor` with `CLIPImageProcessor`. This will certainly not change or break your checkpoint, but onlymake sure that everything is up to date.
Best, the 🧨 Diffusers team.
- model_index.json +5 -5
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@@ -3,20 +3,20 @@
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"_diffusers_version": "0.2.4",
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"feature_extractor": [
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"transformers",
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"
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],
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"safety_checker": [
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"stable_diffusion",
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"StableDiffusionSafetyChecker"
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],
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"text_encoder": [
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"transformers",
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"CLIPTextModel"
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],
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"scheduler": [
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"diffusers",
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"DDIMScheduler"
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],
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"tokenizer": [
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"transformers",
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"CLIPTokenizer"
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"_diffusers_version": "0.2.4",
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"feature_extractor": [
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"transformers",
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"CLIPImageProcessor"
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],
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"safety_checker": [
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"stable_diffusion",
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"StableDiffusionSafetyChecker"
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],
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"scheduler": [
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"diffusers",
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"DDIMScheduler"
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],
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"text_encoder": [
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"transformers",
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"CLIPTextModel"
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],
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"tokenizer": [
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"transformers",
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"CLIPTokenizer"
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