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--- |
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license: apache-2.0 |
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metrics: |
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- bertscore |
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- rouge |
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- bleu |
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pipeline_tag: text-generation |
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language: |
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- en |
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library_name: transformers |
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tags: |
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- Story-Generation |
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- State-Space |
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- text-generation-inference |
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- story-writing |
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--- |
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The State-Space/Mamba-370M is finetuned on ROC Stories dataset to be able to generate endings to short stories cohesively. |
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The Evaluation metrics on the ROC stories dataset for story ending generation are: |
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Bert (f1) : 0.878 |
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Meteor: 0.1 |
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bleu : 0.0125 |
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Rouge1: 0.18 |
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Perplexity : 207 |
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### To use the Model: |
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```python |
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>>> from transformers import MambaForCausalLM, AutoTokenizer |
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>>> model_name = "DdIiVvYyAaMm/mamba-370m-story-generation" |
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>>> tokenizer = AutoTokenizer.from_pretrained(model_name) |
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>>> model = MambaForCausalLM.from_pretrained(model_name) |
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# And the rest of code standard as from transformers library. |
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``` |
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