Instructions to use OpenGVLab/InternVL-Chat-ViT-6B-Vicuna-7B 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-7B 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-7B")# Load model directly from transformers import AutoProcessor, AutoModelForCausalLM processor = AutoProcessor.from_pretrained("OpenGVLab/InternVL-Chat-ViT-6B-Vicuna-7B") model = AutoModelForCausalLM.from_pretrained("OpenGVLab/InternVL-Chat-ViT-6B-Vicuna-7B") - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
b19215a | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:00bafdc63987d735b16ca2916a85a8038f220586d5e6cee07d2e18d77f0415d1
size 59786877
|