Instructions to use davanstrien/clip-roberta-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davanstrien/clip-roberta-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="davanstrien/clip-roberta-finetuned")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("davanstrien/clip-roberta-finetuned") model = AutoModel.from_pretrained("davanstrien/clip-roberta-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from davanstrien/clip-roberta-finetuned: direct link, hf CLI and curl.
- Browser
- Download file 397 Bytes
-
https://huggingface.co/davanstrien/clip-roberta-finetuned/resolve/341bb787a229c6b02f8dd4ad343149706567ea1d/preprocessor_config.json
- Command line
-
hf download hf://davanstrien/clip-roberta-finetuned@341bb787a229c6b02f8dd4ad343149706567ea1d/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/davanstrien/clip-roberta-finetuned/resolve/341bb787a229c6b02f8dd4ad343149706567ea1d/preprocessor_config.json
397 Bytes
| { | |
| "crop_size": 224, | |
| "do_center_crop": true, | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_resize": true, | |
| "feature_extractor_type": "CLIPFeatureExtractor", | |
| "image_mean": [ | |
| 0.48145466, | |
| 0.4578275, | |
| 0.40821073 | |
| ], | |
| "image_std": [ | |
| 0.26862954, | |
| 0.26130258, | |
| 0.27577711 | |
| ], | |
| "processor_class": "VisionTextDualEncoderProcessor", | |
| "resample": 3, | |
| "size": 224 | |
| } | |