Instructions to use d-wang26/wd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use d-wang26/wd with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("d-wang26/wd", 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
Download diffusers/tests/pipelines/test_pipeline_utils.py from d-wang26/wd: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/d-wang26/wd/resolve/main/diffusers/tests/pipelines/test_pipeline_utils.py
- Command line
-
hf download hf://d-wang26/wd/diffusers/tests/pipelines/test_pipeline_utils.py
-
curl -L -o test_pipeline_utils.py https://huggingface.co/d-wang26/wd/resolve/main/diffusers/tests/pipelines/test_pipeline_utils.py
5.5 kB
| import unittest | |
| from diffusers.pipelines.pipeline_utils import is_safetensors_compatible | |
| class IsSafetensorsCompatibleTests(unittest.TestCase): | |
| def test_all_is_compatible(self): | |
| filenames = [ | |
| "safety_checker/pytorch_model.bin", | |
| "safety_checker/model.safetensors", | |
| "vae/diffusion_pytorch_model.bin", | |
| "vae/diffusion_pytorch_model.safetensors", | |
| "text_encoder/pytorch_model.bin", | |
| "text_encoder/model.safetensors", | |
| "unet/diffusion_pytorch_model.bin", | |
| "unet/diffusion_pytorch_model.safetensors", | |
| ] | |
| self.assertTrue(is_safetensors_compatible(filenames)) | |
| def test_diffusers_model_is_compatible(self): | |
| filenames = [ | |
| "unet/diffusion_pytorch_model.bin", | |
| "unet/diffusion_pytorch_model.safetensors", | |
| ] | |
| self.assertTrue(is_safetensors_compatible(filenames)) | |
| def test_diffusers_model_is_not_compatible(self): | |
| filenames = [ | |
| "safety_checker/pytorch_model.bin", | |
| "safety_checker/model.safetensors", | |
| "vae/diffusion_pytorch_model.bin", | |
| "vae/diffusion_pytorch_model.safetensors", | |
| "text_encoder/pytorch_model.bin", | |
| "text_encoder/model.safetensors", | |
| "unet/diffusion_pytorch_model.bin", | |
| # Removed: 'unet/diffusion_pytorch_model.safetensors', | |
| ] | |
| self.assertFalse(is_safetensors_compatible(filenames)) | |
| def test_transformer_model_is_compatible(self): | |
| filenames = [ | |
| "text_encoder/pytorch_model.bin", | |
| "text_encoder/model.safetensors", | |
| ] | |
| self.assertTrue(is_safetensors_compatible(filenames)) | |
| def test_transformer_model_is_not_compatible(self): | |
| filenames = [ | |
| "safety_checker/pytorch_model.bin", | |
| "safety_checker/model.safetensors", | |
| "vae/diffusion_pytorch_model.bin", | |
| "vae/diffusion_pytorch_model.safetensors", | |
| "text_encoder/pytorch_model.bin", | |
| # Removed: 'text_encoder/model.safetensors', | |
| "unet/diffusion_pytorch_model.bin", | |
| "unet/diffusion_pytorch_model.safetensors", | |
| ] | |
| self.assertFalse(is_safetensors_compatible(filenames)) | |
| def test_all_is_compatible_variant(self): | |
| filenames = [ | |
| "safety_checker/pytorch_model.fp16.bin", | |
| "safety_checker/model.fp16.safetensors", | |
| "vae/diffusion_pytorch_model.fp16.bin", | |
| "vae/diffusion_pytorch_model.fp16.safetensors", | |
| "text_encoder/pytorch_model.fp16.bin", | |
| "text_encoder/model.fp16.safetensors", | |
| "unet/diffusion_pytorch_model.fp16.bin", | |
| "unet/diffusion_pytorch_model.fp16.safetensors", | |
| ] | |
| variant = "fp16" | |
| self.assertTrue(is_safetensors_compatible(filenames, variant=variant)) | |
| def test_diffusers_model_is_compatible_variant(self): | |
| filenames = [ | |
| "unet/diffusion_pytorch_model.fp16.bin", | |
| "unet/diffusion_pytorch_model.fp16.safetensors", | |
| ] | |
| variant = "fp16" | |
| self.assertTrue(is_safetensors_compatible(filenames, variant=variant)) | |
| def test_diffusers_model_is_compatible_variant_partial(self): | |
| # pass variant but use the non-variant filenames | |
| filenames = [ | |
| "unet/diffusion_pytorch_model.bin", | |
| "unet/diffusion_pytorch_model.safetensors", | |
| ] | |
| variant = "fp16" | |
| self.assertTrue(is_safetensors_compatible(filenames, variant=variant)) | |
| def test_diffusers_model_is_not_compatible_variant(self): | |
| filenames = [ | |
| "safety_checker/pytorch_model.fp16.bin", | |
| "safety_checker/model.fp16.safetensors", | |
| "vae/diffusion_pytorch_model.fp16.bin", | |
| "vae/diffusion_pytorch_model.fp16.safetensors", | |
| "text_encoder/pytorch_model.fp16.bin", | |
| "text_encoder/model.fp16.safetensors", | |
| "unet/diffusion_pytorch_model.fp16.bin", | |
| # Removed: 'unet/diffusion_pytorch_model.fp16.safetensors', | |
| ] | |
| variant = "fp16" | |
| self.assertFalse(is_safetensors_compatible(filenames, variant=variant)) | |
| def test_transformer_model_is_compatible_variant(self): | |
| filenames = [ | |
| "text_encoder/pytorch_model.fp16.bin", | |
| "text_encoder/model.fp16.safetensors", | |
| ] | |
| variant = "fp16" | |
| self.assertTrue(is_safetensors_compatible(filenames, variant=variant)) | |
| def test_transformer_model_is_compatible_variant_partial(self): | |
| # pass variant but use the non-variant filenames | |
| filenames = [ | |
| "text_encoder/pytorch_model.bin", | |
| "text_encoder/model.safetensors", | |
| ] | |
| variant = "fp16" | |
| self.assertTrue(is_safetensors_compatible(filenames, variant=variant)) | |
| def test_transformer_model_is_not_compatible_variant(self): | |
| filenames = [ | |
| "safety_checker/pytorch_model.fp16.bin", | |
| "safety_checker/model.fp16.safetensors", | |
| "vae/diffusion_pytorch_model.fp16.bin", | |
| "vae/diffusion_pytorch_model.fp16.safetensors", | |
| "text_encoder/pytorch_model.fp16.bin", | |
| # 'text_encoder/model.fp16.safetensors', | |
| "unet/diffusion_pytorch_model.fp16.bin", | |
| "unet/diffusion_pytorch_model.fp16.safetensors", | |
| ] | |
| variant = "fp16" | |
| self.assertFalse(is_safetensors_compatible(filenames, variant=variant)) | |