Instructions to use na1taneja2821/diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use na1taneja2821/diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("na1taneja2821/diffusers") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 826 Bytes
dc0392c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | # Overview
These examples show how to run [Diffuser](https://arxiv.org/abs/2205.09991) in Diffusers.
There are two ways to use the script, `run_diffuser_locomotion.py`.
The key option is a change of the variable `n_guide_steps`.
When `n_guide_steps=0`, the trajectories are sampled from the diffusion model, but not fine-tuned to maximize reward in the environment.
By default, `n_guide_steps=2` to match the original implementation.
You will need some RL specific requirements to run the examples:
```
pip install -f https://download.pytorch.org/whl/torch_stable.html \
free-mujoco-py \
einops \
gym==0.24.1 \
protobuf==3.20.1 \
git+https://github.com/rail-berkeley/d4rl.git \
mediapy \
Pillow==9.0.0
```
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