| import streamlit as st |
| from transformers import AutoTokenizer, AutoModelForCausalLM |
|
|
| |
| model_name = "facebook/opt-125m" |
| tokenizer = AutoTokenizer.from_pretrained(model_name) |
| model = AutoModelForCausalLM.from_pretrained(model_name) |
|
|
| st.title('Text Generation with Hugging Face') |
|
|
| |
| input_text = st.text_input("Enter your prompt:", "sun rises in the ") |
|
|
| if input_text: |
| |
| inputs = tokenizer(input_text, return_tensors="pt") |
|
|
| |
| outputs = model.generate( |
| inputs["input_ids"], |
| max_length=50, |
| num_return_sequences=1, |
| no_repeat_ngram_size=2, |
| top_p=0.95, |
| top_k=50, |
| temperature=0.7 |
| ) |
|
|
| |
| generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True) |
|
|
| |
| st.write("Generated Text:") |
| st.write(generated_text) |
|
|
