Visual Question Answering
Transformers
Safetensors
English
panovlm_decision
feature-extraction
panovlm
decision-model
calibration
fastvit
linear-attention
custom_code
Instructions to use PanocularAI/PanoVLD-500M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PanocularAI/PanoVLD-500M with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "visual-question-answering" 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("visual-question-answering", model="PanocularAI/PanoVLD-500M", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("PanocularAI/PanoVLD-500M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from PanocularAI/PanoVLD-500M: direct link, hf CLI and curl.
- Browser
- Download file 297 Bytes
-
https://huggingface.co/PanocularAI/PanoVLD-500M/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://PanocularAI/PanoVLD-500M/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/PanocularAI/PanoVLD-500M/resolve/main/preprocessor_config.json
297 Bytes
| { | |
| "image_processor_type": "PanoVLMImageProcessor", | |
| "image_size": 768, | |
| "image_resize_mode": "pad", | |
| "image_mean": [ | |
| 0.0, | |
| 0.0, | |
| 0.0 | |
| ], | |
| "image_std": [ | |
| 1.0, | |
| 1.0, | |
| 1.0 | |
| ], | |
| "auto_map": { | |
| "AutoImageProcessor": "image_processing_panovlm.PanoVLMImageProcessor" | |
| } | |
| } |