---
datasets:
- tapaco
metrics:
- bleu
- rouge
- ter
pipeline_tag: text2text-generation
---
from transformers import pipeline

# Load the model from the Hugging Face Model Hub
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    tokenizer = AutoTokenizer.from_pretrained("ihgn/similar-questions")
    model = AutoModelForSeq2SeqLM.from_pretrained("ihgn/similar-questions")
    model = pipeline("text2text-generation", model=model_name)

# Configure the generation parameters
    generation_config = {
        "max_length": 512,
        "num_beams": 1,
        "top_k": 50,
        "top_p": 0.92,
        "do_sample": True,
        "num_return_sequences": 1
    }

# Generate text using the configured parameters
    input_text= "Your input text goes here."
    input_ids = tokenizer.encode(input_text, return_tensors="pt")
    generated_ids = model(input_ids, **generation_config)
    generated_text = tokenizer.decode(generated_ids.squeeze(), skip_special_tokens=True)
# Print the generated text
    print(generated_text)