Instructions to use tranmc/model-diffuser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tranmc/model-diffuser with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("tranmc/model-diffuser", 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 sample_data/mnist_test.csv from tranmc/model-diffuser: direct link, hf CLI and curl.
- Browser
- Download file 18.3 MB
-
https://huggingface.co/tranmc/model-diffuser/resolve/86b768323f43eaa1b4ffdfe03ca85f596e52db30/sample_data/mnist_test.csv
- Command line
-
hf download hf://tranmc/model-diffuser@86b768323f43eaa1b4ffdfe03ca85f596e52db30/sample_data/mnist_test.csv
-
curl -L -o mnist_test.csv https://huggingface.co/tranmc/model-diffuser/resolve/86b768323f43eaa1b4ffdfe03ca85f596e52db30/sample_data/mnist_test.csv
18.3 MB
- Xet hash:
- 4c3587f03c90386f5c109436735436a62788da4696285b74c1bcab09d64d103f
- Size of remote file:
- 18.3 MB
- SHA256:
- 51c292478d94ec3a01461bdfa82eb0885d262eb09e615679b2d69dedb6ad09e7
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