Instructions to use PhilipC/HumanOmniV2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PhilipC/HumanOmniV2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("PhilipC/HumanOmniV2") model = AutoModelForImageTextToText.from_pretrained("PhilipC/HumanOmniV2") - Notebooks
- Google Colab
- Kaggle
Improve model card for HumanOmniV2: Add metadata and comprehensive content
#1
by nielsr HF Staff - opened
This PR enhances the model card for HumanOmniV2 by:
- Adding the
pipeline_tag: video-text-to-textto improve model discoverability on the Hugging Face Hub. - Specifying
library_name: transformers, which enables the "how to use" widget and indicates compatibility. - Setting
license: apache-2.0to clearly state the model's license. - Updating the paper link to include the Hugging Face Papers page.
- Adding a direct link to the GitHub repository for easy access to the code.
- Integrating comprehensive details from the GitHub README, including a full overview, news, experimental results, training and evaluation instructions, and usage examples.
- Correcting image paths to ensure proper rendering on the Hub.
PhilipC changed pull request status to merged