Text-to-Image
Diffusers
ONNX
Safetensors
GGUF
English
art
agent
image-generation
video-generation
text-to-video
style-transfer
image-editing
tts
local-inference
Instructions to use atMrMattV/Visione with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use atMrMattV/Visione with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("atMrMattV/Visione", 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
Download models/kiwi-edit/source_embedder/config.json from atMrMattV/Visione: direct link, hf CLI and curl.
- Browser
- Download file 163 Bytes
-
https://huggingface.co/atMrMattV/Visione/resolve/main/models/kiwi-edit/source_embedder/config.json
- Command line
-
hf download hf://atMrMattV/Visione/models/kiwi-edit/source_embedder/config.json
-
curl -L -o config.json https://huggingface.co/atMrMattV/Visione/resolve/main/models/kiwi-edit/source_embedder/config.json
163 Bytes
| { | |
| "_class_name": "ConditionalEmbedder", | |
| "in_dim": 48, | |
| "dim": 3072, | |
| "patch_size": [ | |
| 1, | |
| 2, | |
| 2 | |
| ], | |
| "zero_init": true, | |
| "ref_pad_first": false | |
| } |