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datasets:
- codeparrot/conala-mined-curated
pipeline_tag: text2text-generation
---
# Model Card for Starcoder-conala
<!-- Provide a quick summary of what the model is/does. -->
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)
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).
## Usage
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
The model was fine-tuned with the following template
```
Question: <instruction>
Answer: <output>
```
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
```python
instruction = "Write a function to compute the GCD between two integers a and b"
prompt = f"Question:{instruction}\n\nAnswer:"
input_ids = tokenizer(prompt, return_tensors="pt")["input_ids"]
completion = model.generate(input_ids, max_length=200)
print(tokenizer.batch_decode(completion[:,input_ids.shape[1]:])[0])
```
## More information
For additional information, check
- [Conala-mined-curated](https://huggingface.co/datasets/codeparrot/conala-mined-curated)
- [Starcoder](https://huggingface.co/bigcode/starcoder) |