Video-Text-to-Text
Transformers
Safetensors
English
llava_llama
multimodal
video-understanding
region-grounding
3d-reasoning
4d-reasoning
perceptual-distillation
nvila
vila
Instructions to use nvidia/4D-RGPT-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/4D-RGPT-8B with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nvidia/4D-RGPT-8B", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "runs/train/NVILA-Lite-8B-4D-dev_v11/model/tmp-checkpoint-300/vision_tower", | |
| "architectures": [ | |
| "SiglipVisionModel" | |
| ], | |
| "attention_dropout": 0.0, | |
| "hidden_act": "gelu_pytorch_tanh", | |
| "hidden_size": 1152, | |
| "image_size": 448, | |
| "intermediate_size": 4304, | |
| "layer_norm_eps": 1e-06, | |
| "model_type": "siglip_vision_model", | |
| "num_attention_heads": 16, | |
| "num_channels": 3, | |
| "num_hidden_layers": 27, | |
| "num_image_tokens": 256, | |
| "patch_size": 14, | |
| "projection_dim": 2048, | |
| "projector_hidden_act": "gelu_fast", | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.46.3", | |
| "vision_use_head": false | |
| } | |