Instructions to use usakha/Prophetnet_multiNews_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use usakha/Prophetnet_multiNews_model 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="usakha/Prophetnet_multiNews_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("usakha/Prophetnet_multiNews_model") model = AutoModelForSeq2SeqLM.from_pretrained("usakha/Prophetnet_multiNews_model") - Notebooks
- Google Colab
- Kaggle
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README.md
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# Training Results
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| Epoch | Training Loss | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu | Gen Len |
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|:----- |:------------ |:--------------- |:-------- | :------- |:-------- |:--------- |:-------- |:--------- |
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1| 2.981200| 2.831641| 0.414500| 0.147000| 0.230700| 0.230600| 0.512800| 140.734900|
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2 |2.800900| 2.789402| 0.417300| 0.148400| 0.231800| 0.231700| 0.516000| 141.158200|
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3 |2.680300| 2.780862| 0.418300| 0.148400| 0.232200| 0.232100| 0.516800| 140.872300|
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