Instructions to use Caraaaaa/text_image_captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Caraaaaa/text_image_captioning with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("image-to-text", model="Caraaaaa/text_image_captioning")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Caraaaaa/text_image_captioning") model = AutoModelForMultimodalLM.from_pretrained("Caraaaaa/text_image_captioning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from Caraaaaa/text_image_captioning: direct link, hf CLI and curl.
- Browser
- Download file 503 Bytes
-
https://huggingface.co/Caraaaaa/text_image_captioning/resolve/00a22ae2f4e5cfeedb8b0882ba49b3e4eb3eb8c3/preprocessor_config.json
- Command line
-
hf download hf://Caraaaaa/text_image_captioning@00a22ae2f4e5cfeedb8b0882ba49b3e4eb3eb8c3/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/Caraaaaa/text_image_captioning/resolve/00a22ae2f4e5cfeedb8b0882ba49b3e4eb3eb8c3/preprocessor_config.json
503 Bytes
| { | |
| "crop_size": { | |
| "height": 224, | |
| "width": 224 | |
| }, | |
| "do_center_crop": true, | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.48145466, | |
| 0.4578275, | |
| 0.40821073 | |
| ], | |
| "image_processor_type": "CLIPImageProcessor", | |
| "image_std": [ | |
| 0.26862954, | |
| 0.26130258, | |
| 0.27577711 | |
| ], | |
| "processor_class": "GitProcessor", | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "shortest_edge": 224 | |
| } | |
| } | |