Instructions to use alexrink/Pegasus_VTSSum_14epochs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alexrink/Pegasus_VTSSum_14epochs 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="alexrink/Pegasus_VTSSum_14epochs")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("alexrink/Pegasus_VTSSum_14epochs") model = AutoModelForSeq2SeqLM.from_pretrained("alexrink/Pegasus_VTSSum_14epochs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| language: | |
| - en | |
| pipeline_tag: summarization | |
| google/pegasus-large trained on sample of VT-SSum (https://github.com/Dod-o/VT-SSum; https://arxiv.org/pdf/1610.02424.pdf)</br> | |
| Sample consists of 600 train, 200 validation, 200 test using categories Computer Science, Data Science, Mathematics</br> | |
| </br> | |
| * Train Loss: ~0.1 | |
| * Validation Loss: ~0.08 | |