Instructions to use schrum2/MarioDiffusion-MiniLM-single-negative0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use schrum2/MarioDiffusion-MiniLM-single-negative0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("schrum2/MarioDiffusion-MiniLM-single-negative0", 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 text_encoder/loading_info.json from schrum2/MarioDiffusion-MiniLM-single-negative0: direct link, hf CLI and curl.
- Browser
- Download file 141 Bytes
-
https://huggingface.co/schrum2/MarioDiffusion-MiniLM-single-negative0/resolve/main/text_encoder/loading_info.json
- Command line
-
hf download hf://schrum2/MarioDiffusion-MiniLM-single-negative0/text_encoder/loading_info.json
-
curl -L -o loading_info.json https://huggingface.co/schrum2/MarioDiffusion-MiniLM-single-negative0/resolve/main/text_encoder/loading_info.json
141 Bytes
| {"text_encoder_name": "sentence-transformers/multi-qa-MiniLM-L6-cos-v1", "tokenizer_name": "sentence-transformers/multi-qa-MiniLM-L6-cos-v1"} |