Instructions to use chainyo/segformer-sidewalk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chainyo/segformer-sidewalk with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="chainyo/segformer-sidewalk")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("chainyo/segformer-sidewalk") model = SegformerForSemanticSegmentation.from_pretrained("chainyo/segformer-sidewalk", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (2ad94b24ea6082321a7ecda1b9e41dc9f115a300) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>865a505
-
add flavors
f178724 -
fix training_loop for flavors
c769ff4 -
fix indentation
a18af9d -
fix push to hub repo depending on model flavor
4ad6bf4 -
fix typo preprocessor config
6a6eb21 -
add config for preprocessor
e900643 -
fix training loop for push to hub
af16e92 -
fix test notebook
90c75b6 -
add model
8370452 -
add config
fcb528d -
add config
56db83f -
add config
5d5f276 -
create training loop
c75c928 -
create pl model
8e87ed1 -
test notebook
0719c14 -
create dataset and dataloader
3110ea7 -
add id2label file
ff6340b -
add gitignore
518ddd3
-
initial commit
dcf6227