Instructions to use nebiberke/medisum-mt5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nebiberke/medisum-mt5-base 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="nebiberke/medisum-mt5-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("nebiberke/medisum-mt5-base") model = AutoModelForSeq2SeqLM.from_pretrained("nebiberke/medisum-mt5-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a3cb5d9c6051eb1a7f66642da4d75ff1aa2227da7a3e1fb4cbf8c295adf93c0
- Size of remote file:
- 5.97 kB
- SHA256:
- 9bae3671d25ff4c6459afc7f056bdcd6cb17b59b277ed935bfbad6ae8da55136
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