Instructions to use Diankun/Spatial-MLLM-subset-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Diankun/Spatial-MLLM-subset-sft with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSeq2SeqLM processor = AutoProcessor.from_pretrained("Diankun/Spatial-MLLM-subset-sft") model = AutoModelForSeq2SeqLM.from_pretrained("Diankun/Spatial-MLLM-subset-sft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Improve model card: Correct pipeline tag, add library name, and link project page
Verified signatureThis PR improves the model card by: - Correcting the `pipeline_tag` to `video-text-to-text`. - Adding `library_name: transformers` - Adding a link to the project page. This update enhances discoverability and provides a more comprehensive description of the model.af33164
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Update README.md
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Upload folder using huggingface_hub
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initial commit
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