Instructions to use yubinH/summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yubinH/summarization with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("yubinH/summarization") model = AutoModelForSeq2SeqLM.from_pretrained("yubinH/summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files- all_results.json +1 -1
- pytorch_model.bin +1 -1
all_results.json
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{"eval_rouge-1": {"r": 0.
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{"eval_rouge-1": {"r": 0.19353568028765572, "p": 0.28219125530843414, "f": 0.2181162218390264}, "eval_rouge-2": {"r": 0.07739460443336638, "p": 0.11310417988746943, "f": 0.08683468504062511}, "eval_rouge-l": {"r": 0.17649746188918294, "p": 0.2582233920926973, "f": 0.19909405213775405}}
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pytorch_model.bin
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size 1200773058
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