Summarization
Transformers
PyTorch
Enawené-Nawé
longt5
text2text-generation
Trained with AutoTrain
Eval Results (legacy)
Instructions to use L-macc/autotrain-Biomedical_sc_summ-1217846144 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use L-macc/autotrain-Biomedical_sc_summ-1217846144 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="L-macc/autotrain-Biomedical_sc_summ-1217846144")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("L-macc/autotrain-Biomedical_sc_summ-1217846144") model = AutoModelForSeq2SeqLM.from_pretrained("L-macc/autotrain-Biomedical_sc_summ-1217846144", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 1217846144
- CO2 Emissions (in grams): 3198.3977
Validation Metrics
- Loss: 2.449
- Rouge1: 38.839
- Rouge2: 10.865
- RougeL: 21.994
- RougeLsum: 33.794
- Gen Len: 120.994
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/L-macc/autotrain-Biomedical_sc_summ-1217846144
- Downloads last month
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Evaluation results
- ROUGE-1 on Blaise-g/SumPubmedtest set self-reported39.409
- ROUGE-2 on Blaise-g/SumPubmedtest set self-reported12.812
- ROUGE-L on Blaise-g/SumPubmedtest set self-reported21.919
- ROUGE-LSUM on Blaise-g/SumPubmedtest set self-reported35.243
- loss on Blaise-g/SumPubmedtest set self-reported2.200
- gen_len on Blaise-g/SumPubmedtest set self-reported133.854