Instructions to use OpenGVLab/InternViT-6B-448px-V1-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenGVLab/InternViT-6B-448px-V1-5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="OpenGVLab/InternViT-6B-448px-V1-5", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenGVLab/InternViT-6B-448px-V1-5", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
InternVL-C and InternVL-G, with InternViT-6B-448px-V1-5
#6
by AdrienVeepee - opened
First, I would like to commend you on the impressive research and work presented with the InternVL / ViT models. The advancements you've achieved are truly remarkable.
I am particularly interested in the presentation you made in Figure 4 of the InternVL paper (https://arxiv.org/pdf/2312.14238), specifically pertaining to the InternVL-C usage (a).
However, based on the information available on Hugging Face, I am having difficulty understanding or locating a code example that demonstrates how to use the model as explained in Figure 4. Could you assist me with this?
Thank you in advance.
Best regards,
AdrienVeepee changed discussion status to closed
Found the details on Github of InternVL