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 added_tokens.json from DAMO-NLP-SG/VideoLLaMA2-72B: direct link, hf CLI and curl.
- Browser
- Download file 80 Bytes
-
https://huggingface.co/DAMO-NLP-SG/VideoLLaMA2-72B/resolve/main/added_tokens.json
- Command line
-
hf download hf://DAMO-NLP-SG/VideoLLaMA2-72B/added_tokens.json
-
curl -L -o added_tokens.json https://huggingface.co/DAMO-NLP-SG/VideoLLaMA2-72B/resolve/main/added_tokens.json
80 Bytes
| { | |
| "<|endoftext|>": 151643, | |
| "<|im_end|>": 151645, | |
| "<|im_start|>": 151644 | |
| } | |