Instructions to use OpenGVLab/InternVL-Chat-ViT-6B-Vicuna-13B-448px with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenGVLab/InternVL-Chat-ViT-6B-Vicuna-13B-448px with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="OpenGVLab/InternVL-Chat-ViT-6B-Vicuna-13B-448px")# Load model directly from transformers import AutoProcessor, AutoModelForCausalLM processor = AutoProcessor.from_pretrained("OpenGVLab/InternVL-Chat-ViT-6B-Vicuna-13B-448px") model = AutoModelForCausalLM.from_pretrained("OpenGVLab/InternVL-Chat-ViT-6B-Vicuna-13B-448px") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 40b482185d8ec8c05a26bc64cbf603cb14a993062ed9cb16302b53cdd940c816
- Size of remote file:
- 85.2 MB
- SHA256:
- 0923911ec928f853f4d93773ae69ed6748bb84fe10a28f3fee7853cc35bbd3e5
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