Instructions to use radna/Triton-InternViT-6B-448px-V1-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use radna/Triton-InternViT-6B-448px-V1-5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="radna/Triton-InternViT-6B-448px-V1-5", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("radna/Triton-InternViT-6B-448px-V1-5", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from radna/Triton-InternViT-6B-448px-V1-5: direct link, hf CLI and curl.
- Browser
- Download file 306 Bytes
-
https://huggingface.co/radna/Triton-InternViT-6B-448px-V1-5/resolve/bb1afdbadbb6314cc8f1ad2106f3ce700a054d67/preprocessor_config.json
- Command line
-
hf download hf://radna/Triton-InternViT-6B-448px-V1-5@bb1afdbadbb6314cc8f1ad2106f3ce700a054d67/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/radna/Triton-InternViT-6B-448px-V1-5/resolve/bb1afdbadbb6314cc8f1ad2106f3ce700a054d67/preprocessor_config.json
306 Bytes
| { | |
| "crop_size": 448, | |
| "do_center_crop": true, | |
| "do_normalize": true, | |
| "do_resize": true, | |
| "feature_extractor_type": "CLIPFeatureExtractor", | |
| "image_mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "image_std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ], | |
| "resample": 3, | |
| "size": 448 | |
| } | |