Instructions to use Hemanth-thunder/stable_diffusion_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Hemanth-thunder/stable_diffusion_lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Hemanth-thunder/stable_diffusion_lora", dtype=torch.bfloat16, device_map="cuda") prompt = "hmat" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download autotrain-advanced/src/autotrain/cli/__init__.py from Hemanth-thunder/stable_diffusion_lora: direct link, hf CLI and curl.
- Browser
- Download file 310 Bytes
-
https://huggingface.co/Hemanth-thunder/stable_diffusion_lora/resolve/main/autotrain-advanced/src/autotrain/cli/__init__.py
- Command line
-
hf download hf://Hemanth-thunder/stable_diffusion_lora/autotrain-advanced/src/autotrain/cli/__init__.py
-
curl -L -o __init__.py https://huggingface.co/Hemanth-thunder/stable_diffusion_lora/resolve/main/autotrain-advanced/src/autotrain/cli/__init__.py
310 Bytes
| from abc import ABC, abstractmethod | |
| from argparse import ArgumentParser | |
| class BaseAutoTrainCommand(ABC): | |
| def register_subcommand(parser: ArgumentParser): | |
| raise NotImplementedError() | |
| def run(self): | |
| raise NotImplementedError() | |