Llamma

app.py

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+import streamlit as st
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+
+# Load the Hugging Face API token from st.secrets
+hf_api_token = st.secrets["HUGGINGFACE_API_TOKEN"]
+
+# Load the model and tokenizer using the API token
+model_name = "meta-llama/Meta-Llama-3.1-405B"
+tokenizer = pipeline('text-generation', model_name, token=hf_api_token)
+
+# Create a text generation pipeline
+generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+# Streamlit UI
+st.title("LLaMA 3.1-405B Model Text Generation")
+st.write(hf_api_token)
+
+# Input prompt
+prompt = st.text_input("Enter your prompt:", value="Explain the significance of the theory of relativity.")
+
+# Generate text on button click
+if st.button("Generate Text"):
+    # Generate text using the pipeline
+    output = generator(prompt, max_length=100, num_return_sequences=1)
+    # Display the generated text
+    st.write(output[0]['generated_text'])

requirements.txt

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+streamlit
+transformers
+torch