fix: fix bibtex format for CodeRL
#5
by zhuwenq - opened
README.md
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@@ -26,6 +26,7 @@ We validate the effectiveness of this checkpoint pretrained with simplified stra
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This model can be easily loaded using the `T5ForConditionalGeneration` functionality:
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```python
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from transformers import AutoTokenizer, T5ForConditionalGeneration
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tokenizer = AutoTokenizer.from_pretrained("Salesforce/codet5-large")
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@@ -50,7 +51,7 @@ print(tokenizer.decode(generated_ids[0], skip_special_tokens=True))
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year = {2021}
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}
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-
@article{CodeRL2022
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author = {Hung Le, Yue Wang, Akhilesh Deepak Gotmare, Silvio Savarese, Steven C.H. Hoi},
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title = {CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning},
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journal = {arXiv preprint},
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This model can be easily loaded using the `T5ForConditionalGeneration` functionality:
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+
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```python
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from transformers import AutoTokenizer, T5ForConditionalGeneration
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tokenizer = AutoTokenizer.from_pretrained("Salesforce/codet5-large")
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year = {2021}
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}
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@article{CodeRL2022,
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author = {Hung Le, Yue Wang, Akhilesh Deepak Gotmare, Silvio Savarese, Steven C.H. Hoi},
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title = {CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning},
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journal = {arXiv preprint},
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