Instructions to use Zamoranesis/clinical_transcripts_roberta_distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Zamoranesis/clinical_transcripts_roberta_distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Zamoranesis/clinical_transcripts_roberta_distilled")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Zamoranesis/clinical_transcripts_roberta_distilled") model = AutoModelForMaskedLM.from_pretrained("Zamoranesis/clinical_transcripts_roberta_distilled", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f78dc1f7d5cd1af6f6c8231e1022880b51470aa4e184558d18234a5ecdfd00ef
- Size of remote file:
- 4.6 kB
- SHA256:
- 2ed10eaa35732be06d286c76dd45e9bccb62ba86827fa15c530fe4dfcd711a30
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