Instructions to use Ram20307/bart-medtranscription with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ram20307/bart-medtranscription with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="Ram20307/bart-medtranscription")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Ram20307/bart-medtranscription") model = AutoModelForSeq2SeqLM.from_pretrained("Ram20307/bart-medtranscription") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 68bec0d23c08c1e1cf274c208141cd16400d5ade16e76bad55390a4a2b62196a
- Size of remote file:
- 5.3 kB
- SHA256:
- 964e1b08683b8e53008c44c260c50e351101da90afa880cb4dfd7189aeacbaae
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