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import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM, set_seed
from transformers import pipeline
import os
description = """# SantaCoder Endpoint"""
token = os.environ["HUB_TOKEN"]
device="cuda:0"
tokenizer = AutoTokenizer.from_pretrained("bigcode/christmas-models", use_auth_token=token)
model = AutoModelForCausalLM.from_pretrained("bigcode/christmas-models", trust_remote_code=True, use_auth_token=token)
def code_generation(gen_prompt, max_tokens, temperature=0.6, seed=42):
set_seed(seed)
pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
generated_text = pipe(gen_prompt, do_sample=True, top_p=0.95, temperature=temperature, max_new_tokens=max_tokens)[0]['generated_text']
return generated_text
import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM, set_seed
from transformers import pipeline
import os
title = "Santa Model Generator"
description = "Demo"
example = [
["def print_hello_world():", 8, 0.6, 42],
["def get_file_size(filepath):", 24, 0.6, 42],
["def count_lines(filename):", 40, 0.6, 42],
["def count_words(filename):", 40, 0.6, 42]]
token = os.environ["HUB_TOKEN"]
device="cuda:0"
revision = "dedup-alt-comments"
tokenizer = AutoTokenizer.from_pretrained("bigcode/christmas-models", use_auth_token=token)
model = AutoModelForCausalLM.from_pretrained("bigcode/christmas-models", revision=revision, trust_remote_code=True, use_auth_token=token)
def code_generation(gen_prompt, max_tokens, temperature=0.6, seed=42):
set_seed(seed)
pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
generated_text = pipe(gen_prompt, do_sample=True, top_p=0.95, temperature=temperature, max_new_tokens=max_tokens)[0]['generated_text']
return generated_text
iface = gr.Interface(
fn=code_generation,
inputs=[
gr.Textbox(lines=10, label="Input code"),
gr.inputs.Slider(
minimum=8,
maximum=1000,
step=1,
default=8,
label="Number of tokens to generate",
),
gr.inputs.Slider(
minimum=0,
maximum=2.5,
step=0.1,
default=0.6,
label="Temperature",
),
gr.inputs.Slider(
minimum=0,
maximum=1000,
step=1,
default=42,
label="Random seed to use for the generation"
)
],
outputs=gr.Textbox(label="Predicted code", lines=10),
examples=example,
layout="horizontal",
theme="peach",
description=description,
title=title
)
iface.launch() |