Video-Text-to-Text
Transformers
Safetensors
minicpmv
feature-extraction
MiniCPM-V
finetune
MLLM
custom_code
Instructions to use xjtupanda/MiniCPM-V-30K-mix-finetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xjtupanda/MiniCPM-V-30K-mix-finetune with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("xjtupanda/MiniCPM-V-30K-mix-finetune", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Improve model card: Add comprehensive summary and usage example
#3
by nielsr HF Staff - opened
This PR enhances the model card by:
- Converting HTML-formatted title and links to standard Markdown.
- Expanding the "Model Summary" section with a detailed abstract and key highlights from the paper and project's GitHub README, providing a clearer understanding of the model's contributions.
- Adding a "How to Use" section with a practical Python code snippet using the
transformerslibrary, demonstrating basic inference and guiding users on handling video inputs.
These improvements aim to make the model card more informative and user-friendly for researchers and practitioners on the Hugging Face Hub.
xjtupanda changed pull request status to merged