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README.md
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# GPT-Code-Clippy-125M-APPS
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## Model Description
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GPT-CC-125M-APPS is a GPT-Neo-1.3B finetuned on APPS dataset. This model is specialized to solve programming tasks.
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## Training data
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[APPS dataset](https://github.com/hendrycks/apps).
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## Training procedure
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The training script used to train this model can be found [here](https://github.com/ncoop57/gpt-code-clippy/blob/camera-ready/training/run_clm_apps.py).
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## Intended Use and Limitations
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The model is finetuned to solve programming problems given a text description and optional starter code.
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### How to use
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You can use this model directly with a pipeline for text generation. This example generates a different sequence each time it's run:
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```py
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from transformers import AutoModelForCausalLM, AutoTokenizer, FlaxAutoModelForCausalLM
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model = AutoModelForCausalLM.from_pretrained("flax-community/gpt-code-clippy-1.3B-apps-alldata")
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tokenizer = AutoTokenizer.from_pretrained("flax-community/gpt-code-clippy-1.3B-apps-alldata")
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prompt = """
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A function to greet user. Given a user name it should say hello
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def greet(name):
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ANSWER:
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"""
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input_ids = tokenizer(prompt, return_tensors='pt').input_ids.to(device)
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start = input_ids.size(1)
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out = model.generate(input_ids, do_sample=True, max_length=50, num_beams=2,
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early_stopping=True, eos_token_id=tokenizer.eos_token_id, )
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print(tokenizer.decode(out[0][start:]))
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```
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### Limitations and Biases
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The model is intended to be used for research purposes and comes with no guarantees of quality of generated code.
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GPT-CC is finetuned GPT-Neo and might have inhereted biases and limitations from it. See [GPT-Neo model card](https://huggingface.co/EleutherAI/gpt-neo-1.3B#limitations-and-biases) for details.
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## Eval results
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Coming soon...
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