Visual Question Answering
Transformers
English
videollama2_mixtral
text-generation
multimodal large language model
large video-language model
Instructions to use DAMO-NLP-SG/VideoLLaMA2-8x7B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DAMO-NLP-SG/VideoLLaMA2-8x7B-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="DAMO-NLP-SG/VideoLLaMA2-8x7B-Base")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("DAMO-NLP-SG/VideoLLaMA2-8x7B-Base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e26dc92570a98cd5eed649de32d3999f79a36ac10c0bcfe7797c12adf357625e
- Size of remote file:
- 978 MB
- SHA256:
- a52095be08a71627df256a870ba9af814dc0fd848d226253f412e4470174b00a
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