Spaces:
Runtime error
Runtime error
import gradio as gr | |
from transformers import AutoTokenizer, AutoModelForCausalLM | |
from peft import PeftModel | |
import torch | |
# πΉ Load tokenizer and base model | |
base_model_id = "deepseek-ai/deepseek-coder-1.3b-base" | |
lora_model_id = "brijmansuriya/deepseek-lora" # β Your LoRA fine-tuned model repo | |
tokenizer = AutoTokenizer.from_pretrained(lora_model_id, trust_remote_code=True) | |
base_model = AutoModelForCausalLM.from_pretrained( | |
base_model_id, | |
device_map="auto", | |
torch_dtype=torch.float16, | |
trust_remote_code=True | |
) | |
# πΉ Load LoRA adapter | |
model = PeftModel.from_pretrained(base_model, lora_model_id) | |
# πΉ Define the function | |
def generate_code(prompt): | |
inputs = tokenizer(prompt, return_tensors="pt").to(model.device) | |
outputs = model.generate( | |
**inputs, | |
max_new_tokens=200, | |
temperature=0.7, | |
do_sample=True, | |
top_p=0.95, | |
) | |
return tokenizer.decode(outputs[0], skip_special_tokens=True) | |
# πΉ Gradio UI | |
demo = gr.Interface( | |
fn=generate_code, | |
inputs=gr.Textbox(label="Enter your coding prompt"), | |
outputs=gr.Textbox(label="Generated Code"), | |
title="π€ DeepSeek Code Generator (LoRA)", | |
description="This app uses DeepSeek-Coder with Brijbhai's fine-tuned LoRA model to generate code from natural language prompts." | |
) | |
demo.launch() | |