Model Card for Self-instruct-starcoder
This model is an instruction-tuned version of βοΈ StarCoder. The instruction dataset involved is Self-instruct-starcoder which was built by boostrapping on StarCoder's generations.
Uses
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
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
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the model is not deployed on the HF Inference API.
Dataset used to train codeparrot/starcoder-self-instruct
Spaces using codeparrot/starcoder-self-instruct 2
Evaluation results
- pass@1 on InstructHumanEvalself-reported0.391
- pass@1 on HumanEvalself-reported0.346