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 pytorch_model.bin from mraottth/trashbot_v1: direct link, hf CLI and curl.
- Browser
- Download file 339 MB
-
https://huggingface.co/mraottth/trashbot_v1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mraottth/trashbot_v1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mraottth/trashbot_v1/resolve/main/pytorch_model.bin
339 MB
- Xet hash:
- 5e936ad8794c98a8d1789d41775fddebfba232725e1fbcda666fc0108d67ca6b
- Size of remote file:
- 339 MB
- SHA256:
- 0e3d3c57b9aa08bd53015292d05131623d12f48a669abb89e339c1cf2afc6419
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