| # Description | |
| CodeT5-small model, fine-tuned on the code summarization subtask of CodeXGLUE (Ruby programming language). This model can generate a docstring of a given function written in Ruby. | |
| # Usage | |
| Here's how to use this model: | |
| ```python | |
| from transformers import RobertaTokenizer, T5ForConditionalGeneration | |
| model_name = "nielsr/codet5-small-code-summarization-ruby" | |
| tokenizer = RobertaTokenizer.from_pretrained(model_name) | |
| model = T5ForConditionalGeneration.from_pretrained(model_name) | |
| code = """ | |
| def update_with_file_contents(digest, filename) | |
| File.open(filename) do |io| | |
| while (chunk = io.read(1024 * 8)) | |
| digest.update(chunk) | |
| end | |
| end | |
| end | |
| """ | |
| input_ids = tokenizer(code, return_tensors="pt").input_ids | |
| outputs = model.generate(input_ids) | |
| print(tokenizer.decode(outputs[0], skip_special_tokens=True)) | |
| # Update the digest with the contents of the given file | |
| ``` |