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:
- f2119dec7406847bd0f6fbf6d85f773129a2034c1b8994c099ea7c7760ac61e4
- Size of remote file:
- 6.08 kB
- SHA256:
- dec9c619a6c102168e8227502b2fde011a97bcd0dc88758ea1f550dce38dd1e6
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