Visual Question Answering
Transformers
English
videollama2_mistral
text-generation
multimodal large language model
large video-language model
Instructions to use DAMO-NLP-SG/VideoLLaMA2-7B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DAMO-NLP-SG/VideoLLaMA2-7B-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="DAMO-NLP-SG/VideoLLaMA2-7B-Base")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("DAMO-NLP-SG/VideoLLaMA2-7B-Base", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b03da2d865ce5e648e397c1f312036d6ae225ac6aa9bf2ed107551526ed8defa
- Size of remote file:
- 978 MB
- SHA256:
- 848b0623c120b5d16d9549884fcad773ca040e9880c2201c98acc497241ac5cd
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