Instructions to use anshuKr/sentence-compression with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anshuKr/sentence-compression 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="anshuKr/sentence-compression")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("anshuKr/sentence-compression") model = AutoModelForSeq2SeqLM.from_pretrained("anshuKr/sentence-compression", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Anshu Kumar commited on
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README.md
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## Getting Started
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### Installation
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2. https://huggingface.co/docs/transformers/en/tasks/summarization
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### Note:
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Download trained checkpoint from given drive link [checkpoint](https://drive.google.com/drive/folders/1yrl0VtmM9BtT4aU2Z5vLs6doz35MMxvM?usp=drive_link)
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datasets:
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- ai4anshu/sentence-compression
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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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## Getting Started
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### Installation
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2. https://huggingface.co/docs/transformers/en/tasks/summarization
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### Note:
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Download trained checkpoint from given drive link [checkpoint](https://drive.google.com/drive/folders/1yrl0VtmM9BtT4aU2Z5vLs6doz35MMxvM?usp=drive_link)
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