Instructions to use crom87/segmentation_test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use crom87/segmentation_test2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="crom87/segmentation_test2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMaskGeneration processor = AutoProcessor.from_pretrained("crom87/segmentation_test2") model = AutoModelForMaskGeneration.from_pretrained("crom87/segmentation_test2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from crom87/segmentation_test2: direct link, hf CLI and curl.
- Browser
- Download file 473 Bytes
-
https://huggingface.co/crom87/segmentation_test2/resolve/main/config.json
- Command line
-
hf download hf://crom87/segmentation_test2/config.json
-
curl -L -o config.json https://huggingface.co/crom87/segmentation_test2/resolve/main/config.json
473 Bytes
| { | |
| "_name_or_path": "facebook/sam-vit-base", | |
| "architectures": [ | |
| "SamModel" | |
| ], | |
| "initializer_range": 0.02, | |
| "mask_decoder_config": { | |
| "model_type": "" | |
| }, | |
| "model_type": "sam", | |
| "prompt_encoder_config": { | |
| "model_type": "" | |
| }, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.40.0.dev0", | |
| "vision_config": { | |
| "dropout": 0.0, | |
| "initializer_factor": 1.0, | |
| "intermediate_size": 6144, | |
| "model_type": "", | |
| "projection_dim": 512 | |
| } | |
| } | |