Summarization
Transformers
PyTorch
Safetensors
Portuguese
t5
text2text-generation
pt-br
abstractive summarization
text-generation-inference
Instructions to use recogna-nlp/ptt5-base-summ-wikilingua with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use recogna-nlp/ptt5-base-summ-wikilingua 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="recogna-nlp/ptt5-base-summ-wikilingua")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("recogna-nlp/ptt5-base-summ-wikilingua") model = AutoModelForSeq2SeqLM.from_pretrained("recogna-nlp/ptt5-base-summ-wikilingua", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 00e07bf3500ca41a554fe2c1ef7ac2c9a092e562c18ee606c45e28880cadfd93
- Size of remote file:
- 892 MB
- SHA256:
- e7355511eea58b0909326748b66ce1b0da30d86bfeb4fc4661ba28c34ac7a078
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