Instructions to use sthui/SimpleSeg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sthui/SimpleSeg with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="sthui/SimpleSeg", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sthui/SimpleSeg", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from sthui/SimpleSeg: direct link, hf CLI and curl.
- Browser
- Download file 401 Bytes
-
https://huggingface.co/sthui/SimpleSeg/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://sthui/SimpleSeg/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/sthui/SimpleSeg/resolve/main/preprocessor_config.json
401 Bytes
| { | |
| "auto_map": { | |
| "AutoImageProcessor": "image_processing_kimi_vl.KimiVLImageProcessor", | |
| "AutoProcessor": "processing_kimi_vl.KimiVLProcessor" | |
| }, | |
| "in_token_limit": 4096, | |
| "patch_size": 14, | |
| "num_pooled_tokens": 1024, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "pad_input": true | |
| } |