Instructions to use eulogik/TinyDoc-VLM-768-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eulogik/TinyDoc-VLM-768-checkpoints with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("eulogik/TinyDoc-VLM-768-checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
TinyDoc-VLM-768-checkpoints (ABANDONED)
Do not use. The 768px retrain failed: the vision tower was dead at initialization (constant output features for any input) while the decoder memorized text. Training was stopped; these step checkpoints are kept only as a record of the failed run.
The 256M 384px base model is also retired (measured OCRBench 0.0%, n=1,000) — see eulogik/TinyDoc-VLM-256M.
The working product of this project is the local grounded-extraction SDK: github.com/eulogik/TinyDoc-VLM.
License: Apache 2.0.
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