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Runtime error
| #from transformers import pipeline | |
| import gradio as gr | |
| #from transformers import AutoTokenizer, AutoModelForCausalLM | |
| ##from os import path | |
| ##MODEL_DIRECTORY = "/models/mrm8488-t5-base-finetuned-emotion" | |
| #tokenizer = AutoTokenizer.from_pretrained("tuner007/pegasus_paraphrase", use_fast=False) | |
| ##if not path.exists(MODEL_DIRECTORY): | |
| #model = AutoModelForCausalLM.from_pretrained("tuner007/pegasus_paraphrase") | |
| ## model.save_pretrained(MODEL_DIRECTORY) | |
| ##else: | |
| ## model = AutoModelWithLMHead.from_pretrained(MODEL_DIRECTORY) | |
| # | |
| def get_emotion(text): | |
| # input_ids = tokenizer.encode(text + '</s>', return_tensors='pt') | |
| # output = model.generate(input_ids=input_ids, max_length=2) | |
| # | |
| # # print(output) | |
| # dec = [tokenizer.decode(ids) for ids in output] | |
| # print(dec) | |
| # label = dec[0] | |
| return text | |
| def parph(name= "paraphrase: This is something which I cannt understand at all."): | |
| #text2text = pipeline("text2text-generation") | |
| ##model_name = 'tuner007/pegasus_paraphrase' | |
| #text2text = pipeline('text2text-generation', model = "Vamsi/T5_Paraphrase_Paws") | |
| ##text2text(name) | |
| test = get_emotion(name) | |
| return test # text2text(name) | |
| iface = gr.Interface(fn=parph, inputs="text", outputs="text") | |
| iface.launch() | |