Visual Question Answering
Transformers
Safetensors
English
videollama2_qwen2
text-generation
multimodal large language model
large video-language model
Instructions to use DAMO-NLP-SG/VideoLLaMA2-72B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DAMO-NLP-SG/VideoLLaMA2-72B with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "visual-question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("visual-question-answering", model="DAMO-NLP-SG/VideoLLaMA2-72B")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("DAMO-NLP-SG/VideoLLaMA2-72B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model-00010-of-00032.safetensors from DAMO-NLP-SG/VideoLLaMA2-72B: direct link, hf CLI and curl.
- Browser
- Download file 4.96 GB
-
https://huggingface.co/DAMO-NLP-SG/VideoLLaMA2-72B/resolve/d239839887b8d167c0dad883ae7e6f7130dfd10a/model-00010-of-00032.safetensors
- Command line
-
hf download hf://DAMO-NLP-SG/VideoLLaMA2-72B@d239839887b8d167c0dad883ae7e6f7130dfd10a/model-00010-of-00032.safetensors
-
curl -L -o model-00010-of-00032.safetensors https://huggingface.co/DAMO-NLP-SG/VideoLLaMA2-72B/resolve/d239839887b8d167c0dad883ae7e6f7130dfd10a/model-00010-of-00032.safetensors
4.96 GB
- Xet hash:
- 6aa38cf9ad46a218a8678e26479135cae6e5987ed1aea6bce0a48dea7b06e6ea
- Size of remote file:
- 4.96 GB
- SHA256:
- 3a49ed3f3da6c21ece35e84979332b9b862b047ca2b5ca21df56024b6a9eedf9
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