Feature Extraction
Transformers
Safetensors
hetero_moe_projspace
mixture-of-experts
heterogeneous
dimension-projection-space
ffn-fusion
custom_code
Instructions to use redmingwei/HeteroMoEProjSpace-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use redmingwei/HeteroMoEProjSpace-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="redmingwei/HeteroMoEProjSpace-v2", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("redmingwei/HeteroMoEProjSpace-v2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download processor_vit/preprocessor_config.json from redmingwei/HeteroMoEProjSpace-v2: direct link, hf CLI and curl.
- Browser
- Download file 325 Bytes
-
https://huggingface.co/redmingwei/HeteroMoEProjSpace-v2/resolve/main/processor_vit/preprocessor_config.json
- Command line
-
hf download hf://redmingwei/HeteroMoEProjSpace-v2/processor_vit/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/redmingwei/HeteroMoEProjSpace-v2/resolve/main/processor_vit/preprocessor_config.json
325 Bytes
| { | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "ViTImageProcessor", | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 224, | |
| "width": 224 | |
| } | |
| } | |