Any-to-Any
Transformers
Safetensors
English
Chinese
qwen2_5_vl
text-generation
text-generation-inference
Instructions to use PaDT-MLLM/PaDT_Pro_7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PaDT-MLLM/PaDT_Pro_7B with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForSeq2SeqLM processor = AutoProcessor.from_pretrained("PaDT-MLLM/PaDT_Pro_7B") model = AutoModelForSeq2SeqLM.from_pretrained("PaDT-MLLM/PaDT_Pro_7B") - Notebooks
- Google Colab
- Kaggle
Improve metadata with `any-to-any` pipeline tag and `transformers` library name
#1
by nielsr HF Staff - opened
This PR updates the model card to accurately reflect the model's versatile capabilities and improve discoverability.
Key changes include:
- Updating
pipeline_tagfromimage-text-to-texttoany-to-anyto better represent the model's ability to generate both textual and diverse visual outputs (like segmentation masks and bounding boxes). - Adding
library_name: transformersto ensure the model benefits from automated code snippets and is correctly identified as compatible with the Hugging Facetransformerslibrary. - Updating the sample usage code snippet's prompt to match the more descriptive example found in the GitHub README.
Please review and merge this PR.
PaDT-MLLM changed pull request status to closed