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import gradio as gr | |
import os | |
from dataclasses import dataclass, asdict | |
from ctransformers import AutoModelForCausalLM, AutoConfig | |
class GenerationConfig: | |
temperature: float | |
top_k: int | |
top_p: float | |
repetition_penalty: float | |
max_new_tokens: int | |
seed: int | |
reset: bool | |
stream: bool | |
threads: int | |
stop: list[str] | |
def format_prompt(user_prompt: str): | |
return f"""### Instruction: | |
{user_prompt} | |
### Response:""" | |
def generate( | |
llm: AutoModelForCausalLM, | |
generation_config: GenerationConfig, | |
user_prompt: str, | |
): | |
"""run model inference, will return a Generator if streaming is true""" | |
return next(llm(format_prompt(user_prompt), **asdict(generation_config)))["text"] | |
config = AutoConfig.from_pretrained( | |
"teknium/Replit-v2-CodeInstruct-3B", context_length=2048 | |
) | |
llm = AutoModelForCausalLM.from_pretrained( | |
os.path.abspath("replit-v2-codeinstruct-3b.q4_1.bin"), | |
model_type="replit", | |
config=config, | |
) | |
generation_config = GenerationConfig( | |
temperature=0.2, | |
top_k=50, | |
top_p=0.9, | |
repetition_penalty=1.0, | |
max_new_tokens=512, # adjust as needed | |
seed=42, | |
reset=True, # reset history (cache) | |
stream=True, # streaming per word/token | |
threads=int(os.cpu_count() / 6), # adjust for your CPU | |
stop=["<|endoftext|>"], | |
) | |
user_prefix = "[user]: " | |
assistant_prefix = f"[assistant]:" | |
title = "Replit-v2-CodeInstruct-3b-ggml" | |
description = "This space is an attempt to run the 4 bit quantized version of 'Replit's CodeInstruct 3B' on a CPU" | |
example_1 = "Write a python script for a function which calculates the factorial of the number inputted by user." | |
example_2 = "Write a python script which prints 'you are logged in' only if the user inputs a number between 1-10" | |
examples = [example_1, example_2] | |
def generate_code(user_input): | |
response = generate(llm, generation_config, user_input) | |
print(response) | |
return response | |
UI = gr.Interface( | |
fn=generate_code, | |
inputs=gr.Textbox(label="user_prompt", placeholder="Ask your queries here...."), | |
outputs=gr.Textbox(label="Assistant"), | |
title=title, | |
description=description, | |
examples=examples | |
) | |
UI.launch() | |
# while True: | |
# user_prompt = input(user_prefix) | |
# generator = generate(llm, generation_config, user_prompt.strip()) | |
# print(assistant_prefix, end=" ", flush=True) | |
# for word in generator: | |
# print(word, end="", flush=True) | |
# print("") |