Instructions to use SherryXTChen/Instruct-CLIP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SherryXTChen/Instruct-CLIP with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SherryXTChen/Instruct-CLIP", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md
Verified signature27fead3 -
Update README.md
Verified signature7317c13 -
Improve model card: Fix pipeline tag, add library name and improve content (#1)
Verified signature- Improve model card: Fix pipeline tag, add library name and improve content (b8ef3ef98f4e85dd5d7075c56f6edf0f502a716d) Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>6c1782a -
Update README.md
Verified signatureb64393c -
Update README.md
Verified signature06748ef
-
Push model using huggingface_hub.
Verified signaturec2acd7f -
initial commit
Verified signature0a18150