upadte the app

app.py

@@ -0,0 +1,28 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from huggingface_hub import login
+
+# Login to Hugging Face (you'll need to set HUGGINGFACE_TOKEN in your Secrets)
+login()
+
+# Load model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.1-70B")
+model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-70B")
+
+def generate_email(context):
+    prompt = f"Generate a professional email based on the following context: {context}"
+    inputs = tokenizer(prompt, return_tensors="pt")
+    outputs = model.generate(**inputs, max_length=300)
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+# Create Gradio interface
+iface = gr.Interface(
+    fn=generate_email,
+    inputs=gr.Textbox(lines=5, label="Context"),
+    outputs=gr.Textbox(label="Generated Email"),
+    title="Email Generator",
+    description="Enter the context, and the app will generate an email using Llama 3.1 70B."
+)
+
+# Launch the app
+iface.launch()

requirements.txt

@@ -0,0 +1,4 @@
+gradio
+transformers
+torch
+huggingface_hub