Video-Text-to-Text
Transformers
Safetensors
English
llava
text-generation
multimodal
vision-language
video understanding
spatial reasoning
visuospatial cognition
qwen
llava-video
Instructions to use nkkbr/ViCA-ScanNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nkkbr/ViCA-ScanNet with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForCausalLM processor = AutoProcessor.from_pretrained("nkkbr/ViCA-ScanNet") model = AutoModelForCausalLM.from_pretrained("nkkbr/ViCA-ScanNet") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -16,7 +16,7 @@ language:
|
|
| 16 |
- en
|
| 17 |
library_name: transformers
|
| 18 |
pipeline_tag: video-text-to-text
|
| 19 |
-
model_name: ViCA-
|
| 20 |
base_model: lmms-lab/LLaVA-Video-7B-Qwen2
|
| 21 |
---
|
| 22 |
## Usage and Full Documentation
|
|
|
|
| 16 |
- en
|
| 17 |
library_name: transformers
|
| 18 |
pipeline_tag: video-text-to-text
|
| 19 |
+
model_name: ViCA-ScanNet-7B
|
| 20 |
base_model: lmms-lab/LLaVA-Video-7B-Qwen2
|
| 21 |
---
|
| 22 |
## Usage and Full Documentation
|