import gradio as gr | |
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
def greet(name): | |
tokenizer = AutoTokenizer.from_pretrained("zjunlp/MolGen") | |
model = AutoModelForSeq2SeqLM.from_pretrained("zjunlp/MolGen") | |
sf_input = tokenizer(name, return_tensors="pt") | |
# beam search | |
#molecules = model.generate(input_ids=sf_input["input_ids"], | |
#sf_output = [tokenizer.decode(g, skip_special_tokens=True, clean_up_tokenization_spaces=True).replace(" ","") for g in molecules] | |
return name | |
iface = gr.Interface(fn=greet, inputs="text", outputs="text") | |
iface.launch() |