Instructions to use ai4stem-uga/G-SciEdBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ai4stem-uga/G-SciEdBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ai4stem-uga/G-SciEdBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ai4stem-uga/G-SciEdBERT") model = AutoModelForMaskedLM.from_pretrained("ai4stem-uga/G-SciEdBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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license: mit
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language:
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---
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## G-SciEdBERT: A Contextualized LLM for Science Assessment Tasks in German
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This model developed a contextualized German Science Education BERT (G-SciEdBERT),
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license: mit
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language:
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metrics:
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- accuracy
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library_name: transformers
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pipeline_tag: text-classification
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tags:
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- Science
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## G-SciEdBERT: A Contextualized LLM for Science Assessment Tasks in German
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This model developed a contextualized German Science Education BERT (G-SciEdBERT),
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