Instructions to use Rakshitaa/Text_summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rakshitaa/Text_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="Rakshitaa/Text_summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Rakshitaa/Text_summarization") model = AutoModelForSeq2SeqLM.from_pretrained("Rakshitaa/Text_summarization") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
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- cnn_dailymail
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tags:
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- summarization
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library_name:
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---
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ARTICLE = """
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You don’t always have to give your boss the finger
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Hindi: hi
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Arabic: ar
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- cnn_dailymail
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tags:
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- summarization
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library_name: transformers
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---
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ARTICLE = """
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You don’t always have to give your boss the finger
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Hindi: hi
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Arabic: ar
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