Instructions to use dlb/MentalBERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dlb/MentalBERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dlb/MentalBERTa")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dlb/MentalBERTa") model = AutoModelForMaskedLM.from_pretrained("dlb/MentalBERTa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e42931bbabcc8b9a8aa3d70650c806359a2baae4717d65c09051fe03ffca59ef
- Size of remote file:
- 3.44 kB
- SHA256:
- 176c8f55300bec2852587e3cf1ca4ea339285348e257270ea455e57d37cd182e
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