Instructions to use usakha/Bart_multiNews_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use usakha/Bart_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/Bart_multiNews_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("usakha/Bart_multiNews_model") model = AutoModelForSeq2SeqLM.from_pretrained("usakha/Bart_multiNews_model") - Notebooks
- Google Colab
- Kaggle
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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 | 2.223100 | 2.038599 | 0.147400 | 0.054800 | 0.113500 | 0.113500 | 0.001400 | 20.000000 |
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| 2 | 2.078100 | 2.009619 | 0.152900 | 0.057800 | 0.117000 | 0.117000 | 0.001600 | 20.000000 |
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| 3 | 1.989000 | 2.006006 | 0.152900 | 0.057300 | 0.116700 | 0.116700 | 0.001700 | 20.000000 |
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