19 lines
1.2 KiB
Markdown
19 lines
1.2 KiB
Markdown
## Reformer Model trained on "Crime and Punishment"
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Crime and Punishment text was taken from `gs://trax-ml/reformer/crime-and-punishment-2554.txt`.
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Model was trained in flax using colab notebook proposed by authors: https://colab.research.google.com/github/google/trax/blob/master/trax/models/reformer/text_generation.ipynb
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Weights were converted to Hugging Face PyTorch `ReformerModelWithLMHead`.
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Model is used as a proof of concept that the forward pass works for a `ReformerModelWithLMHead`.
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Given that the model was trained only for 30mins on a ~0.5M tokens dataset and has only 320 tokens,
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the generation results are reasonable:
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```python
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model = ReformerModelWithLMHead.from_pretrained("patrickvonplaten/reformer-crime-and-punish")
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tok = ReformerTokenizer.from_pretrained("patrickvonplaten/reformer-crime-and-punish")
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tok.decode(model.generate(tok.encode("A few months later", return_tensors="pt"), do_sample=True,temperature=0.7, max_length=100)[0])
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# gives:'A few months later on was more than anything in the flat.
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# “I have already.” “That’s not my notion that he had forgotten him.
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# What does that matter? And why do you mean? It’s only another fellow,” he said as he went out, as though he want'
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```
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