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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() |