Instructions to use mraottth/trashbot_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mraottth/trashbot_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="mraottth/trashbot_v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("mraottth/trashbot_v1") model = SegformerForSemanticSegmentation.from_pretrained("mraottth/trashbot_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from mraottth/trashbot_v1: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/mraottth/trashbot_v1/resolve/main/training_args.bin
- Command line
-
hf download hf://mraottth/trashbot_v1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/mraottth/trashbot_v1/resolve/main/training_args.bin
3.52 kB
- Xet hash:
- 60e61cafaad30224cb8f951f7ee12c78ebb1ed12f4aa5c3c6cefe789ab9413c4
- Size of remote file:
- 3.52 kB
- SHA256:
- b4add39d93dc62c8ce9d0ab6a261d54d57071934a0595a20e5265bdcb9003caa
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