app.py

# Install necessary libraries
# !pip install transformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
import torch

# Model and prompt details
model_name = "mlabonne/llama-2-7b-guanaco"
prompt = "What is a large language model?"

# Load tokenizer and model
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
    model_name,
    torch_dtype=torch.float16,
    device_map="auto",
    offload_folder="offload/folder"  # Replace with the path to the offload folder
)

# Generate text using the provided prompt
sequences = pipeline(
    "text-generation",
    model=model,
    tokenizer=tokenizer,
    device=0,  # Change to the appropriate device index or "cuda" if using GPU
)(
    f'<s>[INST] {prompt} [/INST]',
    do_sample=True,
    top_k=10,
    num_return_sequences=1,
    eos_token_id=tokenizer.eos_token_id,
    max_length=200,
)

# Print the generated text
for seq in sequences:
    print(f"Generated Text: {seq['generated_text']}")