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import gradio as gr
import torch
import os
from PIL import Image
Dir = os.path.dirname(os.path.abspath(__file__))
file = f"{Dir}/1.png"
if not os.path.isfile(file):
open(file, "wb").write(b"")
from transformers import AutoModelForCausalLM, AutoTokenizer, LocalAgent
checkpoint = "cerebras/Cerebras-GPT-1.3B"
agent = LocalAgent.from_pretrained(checkpoint, device_map="auto", torch_dtype=torch.bfloat16, trust_remote_code=True)
def greet1(inp):
if inp:
u = agent.run("generate an image of `text` ", answer=inp)
u.save(file)
return Image.open(file)
def greet(inp):
if inp:
return agent.run("generate an image of `text` ", answer=inp)
iface = gr.Interface(fn=greet, inputs="text", outputs="image")
iface.launch()