Instructions to use acvlab/FantasyVLN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use acvlab/FantasyVLN with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("acvlab/FantasyVLN") model = AutoModelForMultimodalLM.from_pretrained("acvlab/FantasyVLN", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from acvlab/FantasyVLN: direct link, hf CLI and curl.
- Browser
- Download file 350 Bytes
-
https://huggingface.co/acvlab/FantasyVLN/resolve/refs%2Fpr%2F1/preprocessor_config.json
- Command line
-
hf download hf://acvlab/FantasyVLN@refs/pr/1/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/acvlab/FantasyVLN/resolve/refs%2Fpr%2F1/preprocessor_config.json
350 Bytes
| { | |
| "min_pixels": 3136, | |
| "max_pixels": 12845056, | |
| "patch_size": 14, | |
| "temporal_patch_size": 2, | |
| "merge_size": 2, | |
| "image_mean": [ | |
| 0.48145466, | |
| 0.4578275, | |
| 0.40821073 | |
| ], | |
| "image_std": [ | |
| 0.26862954, | |
| 0.26130258, | |
| 0.27577711 | |
| ], | |
| "image_processor_type": "Qwen2VLImageProcessor", | |
| "processor_class": "Qwen2_5_VLProcessor" | |
| } |