Summarization
Transformers
PyTorch
TensorBoard
English
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use DunnBC22/flan-t5-base-text_summarization_data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DunnBC22/flan-t5-base-text_summarization_data 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="DunnBC22/flan-t5-base-text_summarization_data")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("DunnBC22/flan-t5-base-text_summarization_data") model = AutoModelForSeq2SeqLM.from_pretrained("DunnBC22/flan-t5-base-text_summarization_data") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e972bbf089a3ccc3fac4f362ddfa794f0afd73587f7ff03ea64a027e91be38fc
- Size of remote file:
- 3.63 kB
- SHA256:
- dbacf5689c8fa0d5320950f4189dde195ef0804bf983aa7275b9fcf054355285
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