Instructions to use jruaechalar/letras0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jruaechalar/letras0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jruaechalar/letras0", 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 Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from jruaechalar/letras0: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/jruaechalar/letras0/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://jruaechalar/letras0@refs/pr/2/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jruaechalar/letras0/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 1725f9e47619985fb794c512b61299dc23703c58d960c805b71907cb0ee67bf2
- Size of remote file:
- 246 MB
- SHA256:
- bfefc79cb46b2f9cec5b385dc40e673ed17004ea1e895c9e0dde9c4c271b40a6
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