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import gradio as gr
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
def runLLM ():
model = AutoModelForCausalLM.from_pretrained("cyberagent/open-calm-small", device_map="auto", torch_dtype=torch.float16)
tokenizer = AutoTokenizer.from_pretrained("cyberagent/open-calm-small")
inputs = tokenizer("AIによって私達の暮らしは、", return_tensors="pt").to(model.device)
with torch.no_grad():
tokens = model.generate(
**inputs,
max_new_tokens=64,
do_sample=True,
temperature=0.7,
top_p=0.9,
repetition_penalty=1.05,
pad_token_id=tokenizer.pad_token_id,
)
output = tokenizer.decode(tokens[0], skip_special_tokens=True)
#output = "やあやあ"
return output
def display_message():
msg = runLLM()
return msg
iface = gr.Interface(fn=display_message, inputs=None, outputs="text")
iface.launch()
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