datasets:

• codeparrot/self-instruct-starcoder pipeline_tag: text2text-generation metrics:
• code_eval library_name: transformers tags:
• code model-index:
• name: StarCoder-SelfInstruct results:
  • task: type: text-generation dataset: type: openai_humaneval name: InstructHumanEval metrics:
    • name: pass@1 type: pass@1 value: 0.391 verified: false
  • task: type: text-generation dataset: type: openai_humaneval name: HumanEval metrics:
    • name: pass@1 type: pass@1 value: 0.346 verified: false

Model Card for Self-instruct-starcoder

This model is an instruction-tuned version of ⭐️ 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

For additional information, check

• self-intruct-starcoder
• starcoder