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--- |
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datasets: |
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- codeparrot/conala-mined-curated |
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pipeline_tag: text2text-generation |
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--- |
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# Model Card for Starcoder-conala |
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<!-- Provide a quick summary of what the model is/does. --> |
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This model is an instruction-tuned version of ⭐️ StarCoder. The instruction dataset involved is [Conala-mined-curated](https://huggingface.co/datasets/codeparrot/conala-mined-curated) |
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which was built by boostrapping by predicting the column *rewritten_intent* of the mined subset of the [CoNaLa corpus](https://huggingface.co/datasets/neulab/conala). |
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## Usage |
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> |
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The model was fine-tuned with the following template |
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``` |
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Question: <instruction> |
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Answer: <output> |
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``` |
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If you have your model and tokenizer loaded, you can use the following code to make the model generate the right output to a given instruction |
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```python |
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instruction = "Write a function to compute the GCD between two integers a and b" |
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prompt = f"Question:{instruction}\n\nAnswer:" |
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input_ids = tokenizer(prompt, return_tensors="pt")["input_ids"] |
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completion = model.generate(input_ids, max_length=200) |
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print(tokenizer.batch_decode(completion[:,input_ids.shape[1]:])[0]) |
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``` |
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## More information |
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For additional information, check |
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- [Conala-mined-curated](https://huggingface.co/datasets/codeparrot/conala-mined-curated) |
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- [Starcoder](https://huggingface.co/bigcode/starcoder) |
