Instructions to use usakha/Prophetnet_MedPaper_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use usakha/Prophetnet_MedPaper_model 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="usakha/Prophetnet_MedPaper_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("usakha/Prophetnet_MedPaper_model") model = AutoModelForSeq2SeqLM.from_pretrained("usakha/Prophetnet_MedPaper_model") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 2000
Browse files
pytorch_model.bin
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runs/Jun26_17-21-06_6ec4302fc76d/events.out.tfevents.1687800074.6ec4302fc76d.19521.0
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