Instructions to use HTBris/converted with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use HTBris/converted with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("HTBris/converted", 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 novaFurryXL_ilV130_diffusers/text_encoder/model.safetensors from HTBris/converted: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/HTBris/converted/resolve/main/novaFurryXL_ilV130_diffusers/text_encoder/model.safetensors
- Command line
-
hf download hf://HTBris/converted/novaFurryXL_ilV130_diffusers/text_encoder/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/HTBris/converted/resolve/main/novaFurryXL_ilV130_diffusers/text_encoder/model.safetensors
246 MB
- Xet hash:
- e178c4af54bd378732bd48d389f19a0552b232b4bdf771515e53ea928597a469
- Size of remote file:
- 246 MB
- SHA256:
- c9b2f69db0350c66f45a84eb5e0ce62b9630b8cd4f657d82fbf1112910559e99
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.