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README.md

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+# Description
+
+CodeT5-small model, fine-tuned on the code summarization subtask of CodeXGLUE (Ruby programming language).
+
+# 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
+```