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")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("MMADS/RoBERTa-OrgCulture-Classifier") model = AutoModelForMaskedLM.from_pretrained("MMADS/RoBERTa-OrgCulture-Classifier") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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## Environmental Impact
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## Environmental Impact
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## Environmental Impact
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**Minimal**
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** Google Colab GPU
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- **Hours used:** 8
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- **Cloud Provider:** Google
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- **Compute Region:** South Carolina
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## Model Card Authors
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M. Murat Ardag
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## Model Card Contact
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via my personal website. thx
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## Citation
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***If you use this model in your research or applications, please cite it as follows:***
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Ardag, M.M. (2024) RoBERTa-OrgCulture-Classifier (Revision 94b6fdd). HuggingFace. https://doi.org/10.57967/hf/2774
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https://doi.org/10.57967/hf/2794
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