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import gradio as gr | |
from llama_cpp import Llama | |
model = Llama(model_path="CodeLlama_7B_nlp_pp_q8_0.gguf") | |
# These phrases/tokens indicate the start of a pass. For demonstration purposes, it's | |
# safe to assume that these should not be encountered in the output and represent a hallucination. | |
stop = ["@NODES", "@CODE", "@DECL"] | |
def generate(input_text): | |
output = model(input_text, max_tokens=128, stop=stop, echo=True) | |
return output['choices'][0]['text'] | |
input_text = gr.inputs.Textbox(lines= 10, label="Enter your code to autocomplete") | |
output_text = gr.outputs.Textbox(label="Output code") | |
description = "Code generation for NLP++ with CodeLlama" | |
examples = [ | |
'# Find concept named parent under root and print "num" val for each child attribute\n', | |
'L("iter") = getconcept(findroot(), L("parent_con"));\n', | |
'# Match node _noun when preceded by _noun\n' | |
] | |
gr.Interface(fn=generate, inputs=input_text, outputs=output_text, title="CodeLlama for NLP++", description=description, examples=examples).launch() |