Instructions to use PamelaBorelli/flan-t5-base-summarization-pt-br with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PamelaBorelli/flan-t5-base-summarization-pt-br 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="PamelaBorelli/flan-t5-base-summarization-pt-br")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("PamelaBorelli/flan-t5-base-summarization-pt-br") model = AutoModelForSeq2SeqLM.from_pretrained("PamelaBorelli/flan-t5-base-summarization-pt-br") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2b6f62865b41edbcb9539f87cd95f11091a97ae2ed21810d7967846cfe8ff456
- Size of remote file:
- 990 MB
- SHA256:
- 0ea0ad1e14e58019b76835ecfb34a058938259066a43ac14de68beb7003e9037
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