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 # Warning: Pipeline type "visual-question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("visual-question-answering", model="dmis-lab/InternVL3-9B-CVRR", trust_remote_code=True)# pip install -U transformers accelerate # 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
File size: 576 Bytes
a381a62 40600d5 a381a62 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | {
"model_type": "cvrr_merged",
"architectures": [
"CVRRMergedModel"
],
"auto_map": {
"AutoConfig": "configuration_cvrr_merged.CVRRMergedConfig",
"AutoModel": "modeling_cvrr_merged.CVRRMergedModel",
"AutoModelForImageTextToText": "modeling_cvrr_merged.CVRRMergedModel"
},
"release": {
"name": "CVRR-InternVL3-9B",
"base_model": "OpenGVLab/InternVL3-9B",
"ell_star": 35,
"recurrent_layer": 36,
"upper_decoder_start": 37,
"inference_T": 4,
"inference_beta": 0.5,
"format": "cvrr_native_plus_merged_transition_v1"
}
}
|