Instructions to use TensorVizion/SamuraiSilver with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TensorVizion/SamuraiSilver with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("TensorVizion/SamuraiSilver", 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
| license: creativeml-openrail-m | |
| tags: | |
| - text-to-image | |
| ### SamuraiSilver on Stable Diffusion via Dreambooth | |
| #### model by TensorVizion | |
| This your the Stable Diffusion model fine-tuned the SamuraiSilver concept taught to Stable Diffusion with Dreambooth. | |
| It can be used by modifying the `instance_prompt`: **<silver> samurai warriors in shining steel armour ready for battle** | |
| You can also train your own concepts and upload them to the library by using [this notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_dreambooth_training.ipynb). | |
| And you can run your new concept via `diffusers`: [Colab Notebook for Inference](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_dreambooth_inference.ipynb), [Spaces with the Public Concepts loaded](https://huggingface.co/spaces/sd-dreambooth-library/stable-diffusion-dreambooth-concepts) | |
| Here are the images used for training this concept: | |
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