Instructions to use ekazakos/grove with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ekazakos/grove with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("ekazakos/grove", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download processor_config.json from ekazakos/grove: direct link, hf CLI and curl.
- Browser
- Download file 166 Bytes
-
https://huggingface.co/ekazakos/grove/resolve/main/processor_config.json
- Command line
-
hf download hf://ekazakos/grove/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/ekazakos/grove/resolve/main/processor_config.json
166 Bytes
| { | |
| "conv_type": "llava_v1", | |
| "grounding_image_size": 512, | |
| "num_frames": 8, | |
| "processor_class": "GroveProcessor", | |
| "target_fps": 5, | |
| "use_mm_start_end": true | |
| } | |