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README.md
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@@ -88,7 +88,33 @@ Task: a task that was abandoned but should be retried or None if there are
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no abandoned tasks that should be retried.</s>
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```
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This helps the decoder know under what downstream task it is currently being fine tuned in, improving the process.
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# Hyperparameters
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MAX_SOURCE_LENGTH = 256 <br>
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no abandoned tasks that should be retried.</s>
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```
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This helps the decoder know under what downstream task it is currently being fine tuned in, improving the process. However, the paper doesn't clearly define whether or not the token
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is already included in the tokenizer's vocabulary. For safe measure, i manually included the token in the tokenizer's vocabulary using this script:
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```python
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from transformers import AutoTokenizer, T5ForConditionalGeneration
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model_name = "Salesforce/codet5p-220m-bimodal"
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model_path = "/path/to/your/model"
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import os
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os.makedirs(model_path, exist_ok=True)
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# Load base model and tokenizer
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = T5ForConditionalGeneration.from_pretrained(model_name)
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# Add special token(s)
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tokenizer.add_special_tokens({"additional_special_tokens": ["<tdec>"]})
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# Resize embeddings to match new vocab size
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model.resize_token_embeddings(len(tokenizer))
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# Save both to a custom directory or just as a runtime
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tokenizer.save_pretrained(model_path)
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model.save_pretrained(model_path)
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```
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# Hyperparameters
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MAX_SOURCE_LENGTH = 256 <br>
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