Image Segmentation
Transformers
Safetensors
ONNX
TensorRT
deformable_detr
instance-segmentation
refinement
fp16
acr
Instructions to use cmes-deepvision/ACR-instance-segmentaiton-refinement-v1.0.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cmes-deepvision/ACR-instance-segmentaiton-refinement-v1.0.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="cmes-deepvision/ACR-instance-segmentaiton-refinement-v1.0.0")# Load model directly from transformers import AutoImageProcessor, OpenVocabMaskPromptMaskDINO processor = AutoImageProcessor.from_pretrained("cmes-deepvision/ACR-instance-segmentaiton-refinement-v1.0.0") model = OpenVocabMaskPromptMaskDINO.from_pretrained("cmes-deepvision/ACR-instance-segmentaiton-refinement-v1.0.0", device_map="auto") - TensorRT
How to use cmes-deepvision/ACR-instance-segmentaiton-refinement-v1.0.0 with TensorRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle