Image Segmentation
Transformers
Safetensors
background-removal
image-matting
BiRefNet
transparency
camouflage
text-preservation
illustration
rgba
custom_code
Instructions to use egeorcun/lucida with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use egeorcun/lucida with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="egeorcun/lucida", trust_remote_code=True)# Load model directly from transformers import AutoModelForImageSegmentation model = AutoModelForImageSegmentation.from_pretrained("egeorcun/lucida", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 367 Bytes
0c1a283 10674ff | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | {
"_name_or_path": "egeorcun/lucida",
"architectures": [
"BiRefNet"
],
"auto_map": {
"AutoConfig": "BiRefNet_config.BiRefNetConfig",
"AutoModelForImageSegmentation": "birefnet.BiRefNet"
},
"custom_pipelines": {
"image-segmentation": {
"pt": [
"AutoModelForImageSegmentation"
],
"tf": [],
"type": "image"
}
},
"bb_pretrained": false
} |