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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8edb39d2cc91d2484c97ce45e331d2b6600b23bfaef0978c6868eedfa7d9fabe
- Size of remote file:
- 4.16 kB
- SHA256:
- 311ed643c23c09cd295b2d780c56b421f48f7879ffc5670ff2f370b209c4b8a7
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