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from transformers import BloomForCausalLM, AutoTokenizer
import gradio as gr
# Loading and setting up GPT2 Open AI Transformer Model
model_path = './model_path_BLOOM_vf'
model = BloomForCausalLM.from_pretrained(model_path)
tokenizer = AutoTokenizer.from_pretrained(model_path)
def generate_text(inp):
# Encoding the starting point of the sentence we want to predict
input_data = tokenizer.encode(inp, return_tensors='pt')
# Generating Output String
output = model.generate(
input_data,
max_length= 100,
do_sample=True,
top_k=0,
top_p=0.92,
)
return tokenizer.decode(output[0], skip_special_tokens=True)
textbox = gr.Textbox(label="Introduce una o más palabras para generar el texto:", placeholder="Por ejemplo: Los jóvenes", lines=1)
gr.Interface(fn=generate_text,
inputs= textbox,
outputs="text",
examples=[
["Los jóvenes"],
["La economía ha"],
["Los conservadores"],
["Hemos trabajado para"],
["El crimen organizado"],
],
).launch() |