Spaces:
Runtime error
Runtime error
File size: 946 Bytes
efc2ce3 7ff3c49 efc2ce3 20ed203 efc2ce3 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 |
import gradio as gr
import torch
from transformers import AutoTokenizer, EncoderDecoderModel
tokenizer = AutoTokenizer.from_pretrained("monsoon-nlp/es-seq2seq-gender-encoder", model_max_length=256)
model = EncoderDecoderModel.from_encoder_decoder_pretrained(
"monsoon-nlp/es-seq2seq-gender-encoder",
"monsoon-nlp/es-seq2seq-gender-decoder",
max_length=45,
)
def flip(content):
input_ids = torch.tensor(tokenizer.encode(content)).unsqueeze(0)
generated = model.generate(input_ids, decoder_start_token_id=model.config.decoder.pad_token_id)
op = tokenizer.decode(generated.tolist()[0][1:])
if '[SEP]' in op:
return op[:op.index('[SEP]')]
return op
iface = gr.Interface(fn=flip,
inputs=gr.inputs.Textbox(label="Original Spanish text"),
outputs=gr.outputs.Textbox(label="Flipped"),
description="seq2seq built from BETO model - see https://huggingface.co/monsoon-nlp/es-seq2seq-gender-encoder",
)
iface.launch()
|