Create app.py

app.py

@@ -0,0 +1,22 @@
+import streamlit as st
+from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
+
+# Load model and tokenizer
+@st.cache_resource  # Cache the resources to avoid reloading on every run
+def load_model():
+    tokenizer = AutoTokenizer.from_pretrained("mistralai/Codestral-22B-v0.1")
+    model = AutoModelForCausalLM.from_pretrained("mistralai/Codestral-22B-v0.1")
+    return tokenizer, model
+
+tokenizer, model = load_model()
+generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+st.title("Chat with Codestral-22B")
+st.write("Ask a question and get a response from the Codestral-22B model.")
+
+user_input = st.text_input("You: ", "Type your question here...")
+
+if st.button("Send"):
+    with st.spinner("Generating response..."):
+        response = generator(user_input, max_length=100, num_return_sequences=1)
+        st.write("Codestral-22B: " + response[0]["generated_text"])