Summarization
Transformers
PyTorch
Core ML
Safetensors
English
t5
text2text-generation
medical
text-generation-inference
Instructions to use Falconsai/medical_summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Falconsai/medical_summarization 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="Falconsai/medical_summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Falconsai/medical_summarization") model = AutoModelForSeq2SeqLM.from_pretrained("Falconsai/medical_summarization") - Inference
- Notebooks
- Google Colab
- Kaggle
Add medical tag
#3
by davanstrien HF Staff - opened
No description provided.
RealFalconsAI changed pull request status to closed
Hey @RealFalconsAI , to better understand how people use the Hub, could you explain why you didn't want to add this tag to the model's metadata? This metadata is intended to make it easier for people to find appropriate models on the Hub, so it would be helpful to know more about why you didn't want to add this tag to your model.
RealFalconsAI changed pull request status to open
RealFalconsAI changed pull request status to merged
Done