Instructions to use 10ths/FADS_base_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 10ths/FADS_base_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="10ths/FADS_base_model", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForVision2Seq model = AutoModelForVision2Seq.from_pretrained("10ths/FADS_base_model", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from 10ths/FADS_base_model: direct link, hf CLI and curl.
- Browser
- Download file 467 Bytes
-
https://huggingface.co/10ths/FADS_base_model/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://10ths/FADS_base_model/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/10ths/FADS_base_model/resolve/main/preprocessor_config.json
467 Bytes
| { | |
| "auto_map": { | |
| "AutoImageProcessor": "Salesforce/xgen-mm-phi3-mini-instruct-r-v1--image_processing_blip_3.Blip3ImageProcessor" | |
| }, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.48145466, | |
| 0.4578275, | |
| 0.40821073 | |
| ], | |
| "image_processor_type": "Blip3ImageProcessor", | |
| "image_std": [ | |
| 0.26862954, | |
| 0.26130258, | |
| 0.27577711 | |
| ], | |
| "interpolation_mode": "bicubic", | |
| "resize_mode": "squash", | |
| "size": [ | |
| 378, | |
| 378 | |
| ] | |
| } | |