Token Classification
Transformers
Safetensors
English
Vietnamese
gemma4
image-text-to-text
systemone
extraction-model
text-to-typed-output
information-extraction
key-information-extraction
extractive-qa
span-extraction
structured-output
document-ai
multilingual
Instructions to use beyoru/gemmaExtract with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beyoru/gemmaExtract with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="beyoru/gemmaExtract")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("beyoru/gemmaExtract") model = AutoModelForMultimodalLM.from_pretrained("beyoru/gemmaExtract", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 479 Bytes
ece8f84 | 1 2 3 4 5 6 7 8 9 10 11 | gemmaExtract
Copyright (c) 2026 beyoru
This model is a modified version of Gemma 4 E4B (https://huggingface.co/google/gemma-4-E4B-it)
by Google, which is licensed under the Apache License, Version 2.0. A copy of that
license is provided in LICENSE-APACHE-2.0.
Modifications: the model weights were modified and an extraction head was added by beyoru in 2026.
The modified weights, the extraction head and the accompanying code are distributed under
CC BY-NC 4.0 (see LICENSE).
|