Spaces:
Sleeping
Sleeping
File size: 1,106 Bytes
b013073 3c50af5 b013073 3c50af5 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 |
import streamlit as st
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
# Titolo dell'app
st.title("🤖 Chatbot DeepSeek Transformers + Streamlit")
@st.cache_resource
def load_model():
model_name = "deepseek-ai/DeepSeek-Coder-V2-Instruct"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, device_map="auto")
return tokenizer, model
tokenizer, model = load_model()
if "chat_history" not in st.session_state:
st.session_state.chat_history = []
user_input = st.text_input("Scrivi il tuo messaggio:")
if user_input:
st.session_state.chat_history.append(("🧑", user_input))
inputs = tokenizer(user_input, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=256, do_sample=True, temperature=0.7)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
st.session_state.chat_history.append(("🤖", response))
for speaker, msg in st.session_state.chat_history:
st.markdown(f"**{speaker}**: {msg}")
|