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