Instructions to use deepakachu/rsicd_image_captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepakachu/rsicd_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="deepakachu/rsicd_image_captioning")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("deepakachu/rsicd_image_captioning") model = AutoModelForMultimodalLM.from_pretrained("deepakachu/rsicd_image_captioning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download generation_config.json from deepakachu/rsicd_image_captioning: direct link, hf CLI and curl.
- Browser
- Download file 136 Bytes
-
https://huggingface.co/deepakachu/rsicd_image_captioning/resolve/main/generation_config.json
- Command line
-
hf download hf://deepakachu/rsicd_image_captioning/generation_config.json
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curl -L -o generation_config.json https://huggingface.co/deepakachu/rsicd_image_captioning/resolve/main/generation_config.json
136 Bytes
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 101, | |
| "eos_token_id": 102, | |
| "pad_token_id": 0, | |
| "transformers_version": "4.37.0" | |
| } | |