training config

burmesegpt/__init__.py

@@ -0,0 +1 @@
+from .main import BurmeseGpt

burmesegpt/config.py

@@ -0,0 +1,3 @@
+class Config:
+    def __init__(self) -> None:
+        pass

{burmese-gpt → burmesegpt}/data_prep.py

@@ -1,6 +1,13 @@
 # to preps data
 from datasets import load_dataset
-# from torch.utils.data import Dataset
+from torch.utils.data import Dataset
 
 dataset = load_dataset("")
 
+class Data(Dataset):
+    def __init__(self) -> None:
+        super().__init__()
+
+    def forward(self,x):
+        pass
+    

{burmese-gpt → burmesegpt}/main.py

@@ -1,5 +1,10 @@
+from .models import SelfAttention,MLP,GPT
+from .tokenizer import Tokenizer
+from .config import Config 
+from .data_prep import Data
+
 class BurmeseGpt:
-    def __init__(self) -> None:
+    def __init__(self):
         pass
 
     def train(self):
@@ -8,7 +13,7 @@ class BurmeseGpt:
     def generate(self):
         pass
 
-    def load_pretrained(self):
+    def load_pretrained(self,name=""):
         pass
 
     

interfaces/chat.py

@@ -1,19 +0,0 @@
-import streamlit as st
-
-st.title("Burmese GPT")
-
-if "messages" not in st.session_state:
-    st.session_state.messages = []
-
-for message in st.session_state.messages:
-    with st.chat_message(message["role"]):
-        st.markdown(message["content"])
-
-if prompt := st.chat_input("What is up?"):
-    st.chat_message("user").markdown(prompt)
-    st.session_state.messages.append({"role": "user", "content": prompt})
-
-    response = f"Echo: {prompt}"
-    with st.chat_message("assistant"):
-        st.markdown(response)
-    st.session_state.messages.append({"role": "assistant", "content": response})

interfaces/text-stream.py

@@ -1,13 +0,0 @@
-import streamlit as st
-
-st.title("Burmese GPT")
-
-user_input = st.text_area("Enter your text here:", "")
-
-option = st.selectbox(
-    'Select an option:',
-    ('Option 1', 'Option 2', 'Option 3')
-)
-
-if st.button("Generate"):
-    st.write("Generated text will appear here.")

sample.py

@@ -1,3 +1,10 @@
 # sample the texts
+from burmesegpt import BurmeseGpt
 
-out_dir = 'out'
+gpt = BurmeseGpt()
+
+model_name = ''
+
+gpt.load_pretrained(model_name)
+
+gpt.sample()

space.py

@@ -0,0 +1,16 @@
+import streamlit as st
+
+def main():
+    st.title("Simply say Uwu xD")
+
+    video_source = st.sidebar.radio("Select feature:", ("Audio Generator", "Text Predictor",))
+
+    if video_source == "Audio Generator":
+        pass
+
+    else:
+        pass
+
+
+if __name__ == "__main__":
+    main()

training.py

@@ -1,3 +1,7 @@
-# training process
+from burmesegpt import BurmeseGpt
+
+gpt = BurmeseGpt()
+
+gpt.train()
 
 out_dir = 'out'