Instructions to use ModelsLab/RMBG with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelsLab/RMBG with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="ModelsLab/RMBG", trust_remote_code=True)# Load model directly from transformers import AutoModelForImageSegmentation model = AutoModelForImageSegmentation.from_pretrained("ModelsLab/RMBG", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 548 Bytes
24fad5e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | {
"_name_or_path": "briaai/RMBG-1.4",
"architectures": [
"BriaRMBG"
],
"auto_map": {
"AutoConfig": "MyConfig.RMBGConfig",
"AutoModelForImageSegmentation": "briarmbg.BriaRMBG"
},
"custom_pipelines": {
"image-segmentation": {
"impl": "MyPipe.RMBGPipe",
"pt": [
"AutoModelForImageSegmentation"
],
"tf": [],
"type": "image"
}
},
"in_ch": 3,
"model_type": "SegformerForSemanticSegmentation",
"out_ch": 1,
"torch_dtype": "float32",
"transformers_version": "4.38.0.dev0"
}
|