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b291d5e eb77d48 e41f4a0 eb77d48 e41f4a0 eb77d48 e41f4a0 b291d5e eb77d48 b291d5e 6808dee b291d5e eb77d48 b291d5e 6808dee b291d5e eb77d48 b291d5e | 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 34 35 36 37 38 39 40 41 42 43 44 | import streamlit as st
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
st.title("📚 AI Adaptive Learning")
MODEL_ID = "TinyLlama/TinyLlama-1.1B-Chat-v1.0"
@st.cache_resource
def load_model():
tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
if tokenizer.pad_token is None:
tokenizer.pad_token = tokenizer.eos_token
model = AutoModelForCausalLM.from_pretrained(
MODEL_ID,
torch_dtype=torch.float32
)
model.eval()
return tokenizer, model
tokenizer, model = load_model()
user_input = st.text_input("Ask a question:")
if st.button("Submit") and user_input:
with st.spinner("Generating answer..."):
inputs = tokenizer(user_input, return_tensors="pt")
with torch.no_grad():
outputs = model.generate(
**inputs,
max_new_tokens=150,
temperature=0.7,
do_sample=True,
pad_token_id=tokenizer.eos_token_id
)
answer = tokenizer.decode(outputs[0], skip_special_tokens=True)
st.subheader("AI Answer:")
st.write(answer) |