Initial Model with the Dexy Assistant

.gitignore

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+smollm

localmodel.py

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+# pip install transformers
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import streamlit as st
+checkpoint = "HuggingFaceTB/SmolLM-135M-Instruct"
+
+device = "cpu" # for GPU use "gpu" usage or "cpu" for CPU usage
+tokenizer = AutoTokenizer.from_pretrained(checkpoint)
+# for multiple GPUs install accelerate and do `model = AutoModelForCausalLM.from_pretrained(checkpoint, device_map="auto")`
+model = AutoModelForCausalLM.from_pretrained(checkpoint).to(device)
+
+st.title("Dexy Chat Assistant")
+
+# Initialize session state for chat history
+if 'messages' not in st.session_state:
+    st.session_state.messages = []
+
+# Text input for user
+user_name = st.text_input("Your name please?: ", key="user_name")
+user_input = st.text_input("Enter your message:", key="user_input")
+
+if st.button("Send"):
+    if user_input:
+        # Add user message to history
+        st.session_state.messages.append({"role": "user", "content": user_input})
+        
+        # Process with model
+        input_text = tokenizer.apply_chat_template(st.session_state.messages, tokenize=False)
+        encoded = tokenizer(input_text, return_tensors="pt", padding=True)
+        inputs = encoded.input_ids.to(device)
+        attention_mask = encoded.attention_mask.to(device)
+        outputs = model.generate(inputs, attention_mask=attention_mask, max_new_tokens=50, temperature=0.2, top_p=0.9, do_sample=True)
+        response = tokenizer.decode(outputs[0])
+        
+        # Add assistant's response to history
+        st.session_state.messages.append({"role": "assistant", "content": response})
+        
+    # Display full chat history
+    for msg in st.session_state.messages:
+        if msg["role"] == "user":
+            st.write(f"{user_name}: {msg['content']}")
+        else:
+            # st.write(f"Dexy: {msg['content']}")
+            st.write(f"Dexy: {msg['content'].split('<|im_start|>assistant')[-1].split('<|im_end|>')[0]}")

requirements.txt

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+transformers
+streamlit