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:
- 8cc860f0d0a368b6abd033b9e0eb08d6f00fe4df2c48e10bbce82264df9a0bab
- Size of remote file:
- 990 MB
- SHA256:
- 211d5468d130271ae6952b6e68409d1d3c6b9a84a1bc9b4242b217b3ec1fe679
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