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
- Xet hash:
- b2141995eb81eb3f0cd35d9514c7adce04d5e24953568445f43432c108a36b11
- Size of remote file:
- 2.48 MB
- SHA256:
- bcacff3229854f5103ee7a85473a30ca9a8b3a68f3aae9b7479574b23ac2256b
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