Summarization
Transformers
PyTorch
Enawené-Nawé
t5
text2text-generation
Trained with AutoTrain
text-generation-inference
Instructions to use aszfcxcgszdx/reverse-summarizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aszfcxcgszdx/reverse-summarizer 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="aszfcxcgszdx/reverse-summarizer")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("aszfcxcgszdx/reverse-summarizer") model = AutoModelForSeq2SeqLM.from_pretrained("aszfcxcgszdx/reverse-summarizer") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Reverse-Summarization
- Model ID: 40852105646
- CO2 Emissions (in grams): 0.0159
Given a headline, the model will attempt to generate an article that pairs well with the headline.
Validation Metrics
- Loss: 2.577
- Rouge1: 19.482
- Rouge2: 6.359
- RougeL: 15.465
- RougeLsum: 17.852
- Gen Len: 18.956
Usage
You can use cURL to access this model:
$ curl -X POST -H "Authorization: Bearer YOUR_HUGGINGFACE_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/aszfcxcgszdx/autotrain-reverse-sum-40852105646
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