Instructions to use jinofcoolnes/sammod with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jinofcoolnes/sammod with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jinofcoolnes/sammod", 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
- Draw Things
- DiffusionBee
model_index.json
Can you please add a model_index.json so we can use it via Colab?
I would love to if I knew how. If you know how please tell me, so I can add it quickly!
Here is the example of the Waifu Diffusion model_Index code:
{
"_class_name": "StableDiffusionPipeline",
"_diffusers_version": "0.4.1",
"feature_extractor": [
"transformers",
"CLIPFeatureExtractor"
],
"safety_checker": [
"stable_diffusion",
"StableDiffusionSafetyChecker"
],
"scheduler": [
"diffusers",
"LMSDiscreteScheduler"
],
"text_encoder": [
"transformers",
"CLIPTextModel"
],
"tokenizer": [
"transformers",
"CLIPTokenizer"
],
"unet": [
"diffusers",
"UNet2DConditionModel"
],
"vae": [
"diffusers",
"AutoencoderKL"
]
}
And here is an example of the Arcane model:
{
"_class_name": "StableDiffusionPipeline",
"_diffusers_version": "0.7.0.dev0",
"feature_extractor": [
"transformers",
"CLIPFeatureExtractor"
],
"safety_checker": [
"stable_diffusion",
"StableDiffusionSafetyChecker"
],
"scheduler": [
"diffusers",
"LMSDiscreteScheduler"
],
"text_encoder": [
"transformers",
"CLIPTextModel"
],
"tokenizer": [
"transformers",
"CLIPTokenizer"
],
"unet": [
"diffusers",
"UNet2DConditionModel"
],
"vae": [
"diffusers",
"AutoencoderKL"
]
}
I think in notepad you should only add that code with the Diffusers Version that you used and saves as model_index.json
i'll see what I can do