Summarization
Transformers
PyTorch
TensorBoard
English
pegasus
text2text-generation
Generated from Trainer
Instructions to use ChaniM/tst-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChaniM/tst-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="ChaniM/tst-summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ChaniM/tst-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("ChaniM/tst-summarization") - Notebooks
- Google Colab
- Kaggle
Update README.md
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by sudoLife - opened
README.md
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model-index:
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- name: tst-summarization
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- Transformers 4.28.0
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- Pytorch 1.13.1+cu117
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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model-index:
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- name: tst-summarization
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results: []
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language:
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- en
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metrics:
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- rouge
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library_name: transformers
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pipeline_tag: summarization
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- Transformers 4.28.0
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- Pytorch 1.13.1+cu117
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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