GenAifeatures / app.py
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# Install required libraries
pip install transformers huggingface_hub gradio torch
# Import necessary modules
from huggingface_hub import login
from transformers import AutoTokenizer, AutoModelForCausalLM
# Log in to Hugging Face (replace 'your_token' with your actual Hugging Face token)
login("your_huggingface_token")
# Load the tokenizer and model from Hugging Face
tokenizer = AutoTokenizer.from_pretrained("Salesforce/codegen-350M-multi")
model = AutoModelForCausalLM.from_pretrained("Salesforce/codegen-350M-multi")
# Input text for code generation
text = "def bubble_sort(list_elements):"
# Tokenize the input text
input_ids = tokenizer(text, return_tensors="pt").input_ids
# Generate code based on the input text
generated_ids = model.generate(
input_ids,
max_length=200, # Adjust as needed
num_return_sequences=1, # Number of generated sequences to return
pad_token_id=tokenizer.eos_token_id # Handle padding tokens
)
# Decode the generated tokens to text
generated_code = tokenizer.decode(generated_ids[0], skip_special_tokens=True)
# Output the generated code
print(generated_code)