Text-to-Image
Diffusers
TensorBoard
Safetensors
stable-diffusion
stable-diffusion-diffusers
custom-diffusion
Instructions to use SidXXD/encoder_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/encoder_1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SidXXD/encoder_1", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a <v1*> cat" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-250/optimizer.bin from SidXXD/encoder_1: direct link, hf CLI and curl.
- Browser
- Download file 609 MB
-
https://huggingface.co/SidXXD/encoder_1/resolve/main/checkpoint-250/optimizer.bin
- Command line
-
hf download hf://SidXXD/encoder_1/checkpoint-250/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/SidXXD/encoder_1/resolve/main/checkpoint-250/optimizer.bin
609 MB
- Xet hash:
- 589d9dc147a68e6fafce9a2acb0495e47beaeb478270e291e6897fbd47b998f1
- Size of remote file:
- 609 MB
- SHA256:
- 1cb147a5b63ad1e0dda29a0853dcd629a2179a40da6a377b28b9a983cccf56ba
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