Instructions to use MMADS/RoBERTa-OrgCulture-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MMADS/RoBERTa-OrgCulture-Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="MMADS/RoBERTa-OrgCulture-Classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("MMADS/RoBERTa-OrgCulture-Classifier") model = AutoModelForMaskedLM.from_pretrained("MMADS/RoBERTa-OrgCulture-Classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Verified signatureFisher et al. (2014) studied organizational practices in six different countries and found that they consistently comprised of (1) employee-orientation, (2) formalization, and (3) innovation practices. The dataset includes 1.3M sentences from employee reviews and 16K sentences from company mission and vision statements. This multi-label model can predict the importance of these three dimensions at the sentence level. It is recommended to tokenize the text into sentences and then aggregate the data to determine the total number of mentions of the three dimensions. ***See***: Fischer, R., Ferreira, M. C., Assmar, E. M. L., Baris, G., Berberoglu, G., Dalyan, F., Wong, C. C., Hassan, A., Hanke, K., & Boer, D. (2014). Organizational practices across cultures: An exploration in six cultural contexts. *International Journal of Cross Cultural Management*, *14*(1), 105-125. https://doi.org/10.1177/1470595813510644f9aed58 -
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