Instructions to use microsoft/dit-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/dit-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, BeitForMaskedImageModeling processor = AutoImageProcessor.from_pretrained("microsoft/dit-base") model = BeitForMaskedImageModeling.from_pretrained("microsoft/dit-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
12 days ago
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Add upstream DiT MIT license information
Verified signatureThe model card currently omits license metadata and the repository has no license file. This adds the MIT license information from the upstream [Microsoft UniLM DiT project](https://github.com/microsoft/unilm/tree/31c5b904ca1bf2afb4c234a6675c683a4e5fc7cd/dit). - Add `license: mit` to the model-card metadata. - Add the upstream MIT `LICENSE`, preserving Microsoft's copyright notice and the full license text (line endings normalized to LF). - Add a model-card License section linking to the local license and its pinned upstream source. Source: [UniLM LICENSE](https://github.com/microsoft/unilm/blob/31c5b904ca1bf2afb4c234a6675c683a4e5fc7cd/LICENSE). The [upstream README](https://github.com/microsoft/unilm/blob/31c5b904ca1bf2afb4c234a6675c683a4e5fc7cd/README.md#license) identifies this root license as the project license, and DiT has no separate license file. Validation: Hugging Face model-card validation passed; license content matches the pinned upstream file after normalizing line end…2e98af0
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