Video-Text-to-Text
Transformers
Safetensors
English
idefics2
text-classification
text-generation-inference
Instructions to use TIGER-Lab/VideoScore-v1.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TIGER-Lab/VideoScore-v1.1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("TIGER-Lab/VideoScore-v1.1") model = AutoModelForSequenceClassification.from_pretrained("TIGER-Lab/VideoScore-v1.1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from TIGER-Lab/VideoScore-v1.1: direct link, hf CLI and curl.
- Browser
- Download file 92 Bytes
-
https://huggingface.co/TIGER-Lab/VideoScore-v1.1/resolve/main/added_tokens.json
- Command line
-
hf download hf://TIGER-Lab/VideoScore-v1.1/added_tokens.json
-
curl -L -o added_tokens.json https://huggingface.co/TIGER-Lab/VideoScore-v1.1/resolve/main/added_tokens.json
92 Bytes
| { | |
| "<end_of_utterance>": 32002, | |
| "<fake_token_around_image>": 32000, | |
| "<image>": 32001 | |
| } | |