Visual Question Answering
Transformers
Safetensors
cvrr_merged
feature-extraction
cvrr
custom_code
latent-reasoning
Instructions to use dmis-lab/InternVL3-9B-CVRR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dmis-lab/InternVL3-9B-CVRR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="dmis-lab/InternVL3-9B-CVRR", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dmis-lab/InternVL3-9B-CVRR", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| from transformers import PretrainedConfig | |
| class CVRRMergedConfig(PretrainedConfig): | |
| model_type = 'cvrr_merged' | |
| def __init__(self, release=None, **kwargs): | |
| super().__init__(**kwargs) | |
| self.release = {} if release is None else release | |
| self.architectures = ['CVRRMergedModel'] | |
| self.auto_map = { | |
| 'AutoConfig': 'configuration_cvrr_merged.CVRRMergedConfig', | |
| 'AutoModel': 'modeling_cvrr_merged.CVRRMergedModel', | |
| 'AutoModelForImageTextToText': 'modeling_cvrr_merged.CVRRMergedModel', | |
| } | |
| CVRRMergedConfig.register_for_auto_class() | |