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
- Xet hash:
- c6c62d9f58238b783f55f731dab9d94c5f587810b68c995afe93d81151169a9d
- Size of remote file:
- 242 MB
- SHA256:
- e0fe7eebcf12d9005087f2420c0eec51143a04cd2c9e57c6965129219198672a
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