Instructions to use OpenGVLab/VideoChat-TPO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenGVLab/VideoChat-TPO with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenGVLab/VideoChat-TPO", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download third_party/cgdetr/standalone_eval/eval_sample.sh from OpenGVLab/VideoChat-TPO: direct link, hf CLI and curl.
- Browser
- Download file 363 Bytes
-
https://huggingface.co/OpenGVLab/VideoChat-TPO/resolve/refs%2Fpr%2F2/third_party/cgdetr/standalone_eval/eval_sample.sh
- Command line
-
hf download hf://OpenGVLab/VideoChat-TPO@refs/pr/2/third_party/cgdetr/standalone_eval/eval_sample.sh
-
curl -L -o eval_sample.sh https://huggingface.co/OpenGVLab/VideoChat-TPO/resolve/refs%2Fpr%2F2/third_party/cgdetr/standalone_eval/eval_sample.sh
363 Bytes
| # Usage: bash standalone_eval/eval_sample.sh | |
| submission_path=standalone_eval/sample_val_preds.jsonl | |
| gt_path=data/highlight_val_release.jsonl | |
| save_path=standalone_eval/sample_val_preds_metrics.json | |
| PYTHONPATH=$PYTHONPATH:. python standalone_eval/eval.py \ | |
| --submission_path ${submission_path} \ | |
| --gt_path ${gt_path} \ | |
| --save_path ${save_path} | |