Instructions to use morpheushoc/InternVideo2-Cls-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use morpheushoc/InternVideo2-Cls-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="morpheushoc/InternVideo2-Cls-8B", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("morpheushoc/InternVideo2-Cls-8B", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| from transformers.configuration_utils import PretrainedConfig | |
| from easydict import EasyDict as MyEasyDict | |
| class VideoChat2Config(PretrainedConfig): | |
| model_type = 'InternVideo2_Classification' | |
| def __init__( | |
| self, | |
| model_config=None, | |
| **kwargs): | |
| super().__init__(**kwargs) | |
| self.model_config = MyEasyDict(model_config) | |
| # class VideoChat2Config(PretrainedConfig): | |
| # model_type = 'InternVideo2_Classification_test' | |
| # def __init__(self,**kwargs): | |
| # super().__init__(**kwargs) |