--- license: mit datasets: - codeparrot/codeparrot-clean tags: - text-generation - code-generation - gpt2-large widget: - text: >- def hello_world(): example_title: Code Generation Example 1 - text: >- example_title: Code Generation Example 2 pipeline_tag: text-generation inference: parameters: max_new_tokens: 30 temperature: 0.5 num_return_sequences: 1 do_sample: true --- # Code Generation using GPT2-Large This is a GPT2-large model that's further fine-tuned on the Codeparrot clean dataset with a custom metric focused on code generation.
I've further trained the tokenizer initialized from the GPT2-large on the same dataset to better align the tokenization for generating code. ## Model description This Model has the same architecture and Parameters as the GPT2-large model. Please refer to this [link](https://d4mucfpksywv.cloudfront.net/better-language-models/language-models.pdf) to know more about the model details. ## Intended Use & Limitations This model is intended to generate code for the required function based on a small description of the output required.
**Note:** The model is primarily trained with an objective of code generation. ## Usage You can use this model directly to get the summaries: ```python import torch from transformers import AutoTokenizer, AutoModelForCausalLM # Load Code Generator LLM and tokenizer from checkpoint tokenizer = AutoTokenizer.from_pretrained("DeathReaper0965/gpt2_large_code_generator") model = AutoModelForCausalLM.from_pretrained("DeathReaper0965/gpt2_large_code_generator") model = model.to("cuda" if torch.cuda.is_available() else "cpu") inputs = tokenizer("def hello_world():", return_tensors="pt").to("cuda" if torch.cuda.is_available() else "cpu") outputs = model.generate(**inputs, max_new_tokens= 30, temperature= 0.5, num_return_sequences= 1) print(tokenizer.batch_decode(outputs)[0]) ###########OUTPUT########### def hello_world(): return "Hello World!" @app.route("/hello_world") def hello_world(): return "Hello World!" ``` > Designed and Developed with by [Praneet](https://deathreaper0965.github.io/) | [LinkedIn](http://linkedin.com/in/deathreaper0965) | [GitHub](https://github.com/DeathReaper0965/)