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-16F-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-16F-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-16F-Base")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("DAMO-NLP-SG/VideoLLaMA2-7B-16F-Base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66c0e89b1c66a5302a6fbb916c8058a34df3b28b9505a66c50c8da3c3adbfba5
- Size of remote file:
- 978 MB
- SHA256:
- d49e42b8a43ee308d2856ebe0b7d7fd9aa7fe7b46426d072b22fef529ef1b02f
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