Instructions to use mlaricheva/roberta-psych with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlaricheva/roberta-psych with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mlaricheva/roberta-psych")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mlaricheva/roberta-psych") model = AutoModelForMaskedLM.from_pretrained("mlaricheva/roberta-psych") - Notebooks
- Google Colab
- Kaggle
| # roberta-psych | |
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| language: en | |
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| This is a [RoBERTa](https://arxiv.org/pdf/1907.11692.pdf) model pretrained on Alexander Street Database of Counselling and Psychotherapy Transcripts (see more about database and its content [here](https://alexanderstreet.com/products/counseling-and-psychotherapy-transcripts-series)). | |
| Further information about training, parameters and evaluation is available in our [paper](https://arxiv.org/abs/2208.06525): | |
| Laricheva, M., Zhang, C., Liu, Y., Chen, G., Tracey, T., Young, R., & Carenini, G. (2022). Automated Utterance Labeling of Conversations Using Natural Language Processing. arXiv preprint arXiv:2208.06525 | |
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| license: cc-by-nc-sa-2.0 | |
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