Update app.py

app.py

@@ -1,4 +1,74 @@
+from contextlib import nullcontext
+import torch
+import tiktoken
+from model import GPTConfig, GPT
 import streamlit as st
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+# -----------------------------------------------------------------------------
+st.set_page_config(page_title="Translation Demo", page_icon=":milky_way:", layout="wide")
+st.subheader("Gerador Canções de musica brasileira")
+
+# ----------------------------------------------
+max_new_tokens = 200 # number of tokens generated in each sample
+temperature = 0.8 # 1.0 = no change, < 1.0 = less random, > 1.0 = more random, in predictions
+top_k = 200 
+seed = 1337
+device = 'cpu' 
+dtype = 'bfloat16' 
+# -----------------------------------------------------------------------------
+
+ptdtype = {'float32': torch.float32, 'bfloat16': torch.bfloat16, 'float16': torch.float16}[dtype]
+ctx = nullcontext() 
+checkpoint = torch.load('ckpt.pt', map_location='cpu')
+gptconf = GPTConfig(**checkpoint['model_args'])
+model = GPT(gptconf)
+state_dict = checkpoint['model']
+model.load_state_dict(state_dict)
+
+
+
+def gera_texto(start, temperature, max_new_tokens, seed, num_samples):
+    torch.manual_seed(seed)
+    enc = tiktoken.get_encoding("gpt2")
+    encode = lambda s: enc.encode(s, allowed_special={"\n"})
+    decode = lambda l: enc.decode(l)
+
+
+    # encode the beginning of the prompt
+    start_ids = encode(start)
+    x = (torch.tensor(start_ids, dtype=torch.long, device='cpu')[None, ...])
+
+    # run generation
+    geracoes = ""
+    with torch.no_grad():
+        with ctx:
+            for k in range(num_samples):
+                y = model.generate(x, max_new_tokens, temperature=temperature, top_k=top_k)
+                geracoes =  decode(y[0].tolist())
+                st.text_area("Gerado {}".format(k+1), value= geracoes, height=300, placeholder="")
+                
+with st.form("my_form"):
+    col1, col2, col3, col4 = st.columns(4)
+    with col1:
+        int_samples = st.slider('Exemplos', min_value=1, max_value=10, value=5, step=1)
+    with col2:
+        int_seed = st.slider('Seed', min_value=1, max_value=1500, value=1337, step=1)
+    with col3:
+        int_size = st.slider('Num Tokens', min_value=20, max_value=500, value=160, step=5)
+    with col4:
+        int_temp = st.number_input("Temperatura",min_value=0.1,max_value=2.0,value=0.8,step=0.1,format="%.1f")
+
+    source = st.text_area("Escolha uma frase inicial", value="Voce e tao linda", placeholder="Entre com o inicio da musica...")
+
+    submitted = st.form_submit_button("Gerar músicas")
+    if submitted:
+        with st.spinner("Gerando exemplos ..."):
+            gera_texto(source,int_temp,int_size,int_seed, int_samples)
+        
+st.write("8 milhões de tokens, 16 camadas de atenção. Três dias de treinamento from stratch")
+st.write("A preparação dos dados demorou um longo final de semana.")
+st.write("Agradecimentos ao [Gabriel](https://www.linkedin.com/in/go2035/) pela ajuda no scrap.")
+st.markdown("""---""")
+original_title = '<p style="font-family:Verdana; color:Blue; font-size: 12px;">Gosta de IA ou é um maker por natureza ? Conecte-se ao meu <a href=https://www.linkedin.com/in/israeloliveira2035/> linkedin</a> e vamos conversar  !</p>'
+st.markdown(original_title, unsafe_allow_html=True)
+st.write("Made with [nanoGPT](https://github.com/karpathy/nanoGPT) e [ColabPro+](https://colab.research.google.com/signup)")