Instructions to use TIGER-Lab/VideoScore-Qwen2-VL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TIGER-Lab/VideoScore-Qwen2-VL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TIGER-Lab/VideoScore-Qwen2-VL")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("TIGER-Lab/VideoScore-Qwen2-VL") model = AutoModelForSequenceClassification.from_pretrained("TIGER-Lab/VideoScore-Qwen2-VL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 317 Bytes
3bc1c64 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"attn_implementation": "flash_attention_2",
"bos_token_id": 151643,
"do_sample": true,
"eos_token_id": [
151645,
151643
],
"num_labels": 5,
"pad_token_id": 151643,
"problem_type": "regression",
"temperature": 0.01,
"top_k": 1,
"top_p": 0.001,
"transformers_version": "4.45.0.dev0"
}
|