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:
# 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") - Notebooks
- Google Colab
- Kaggle
File size: 1,041 Bytes
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"additional_special_tokens": [
{
"content": "<fake_token_around_image>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
{
"content": "<image>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
{
"content": "<end_of_utterance>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
}
],
"bos_token": {
"content": "<s>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
"eos_token": {
"content": "</s>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
"pad_token": {
"content": "<unk>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
"unk_token": {
"content": "<unk>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
}
}
|