test

app.py

@@ -1,69 +1,69 @@
-# import gradio as gr
-# from transformers import AutoTokenizer, AutoModelForCausalLM
-# import torch
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
 
-# # Model initialization
-# model_name = "gpt2"  # or your specific model
-# tokenizer = AutoTokenizer.from_pretrained(model_name)
-# model = AutoModelForCausalLM.from_pretrained(model_name)
+# Model initialization
+model_name = "gpt2"  # or your specific model
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
 
-# # Add special tokens for languages
-# special_tokens = {"additional_special_tokens": ["[YORUBA]", "[IGBO]", "[HAUSA]"]}
-# tokenizer.add_special_tokens(special_tokens)
-# model.resize_token_embeddings(len(tokenizer))
+# Add special tokens for languages
+special_tokens = {"additional_special_tokens": ["[YORUBA]", "[IGBO]", "[HAUSA]"]}
+tokenizer.add_special_tokens(special_tokens)
+model.resize_token_embeddings(len(tokenizer))
 
-# # Move model to GPU if available
-# device = "cuda" if torch.cuda.is_available() else "cpu"
-# model.to(device)
+# Move model to GPU if available
+device = "cuda" if torch.cuda.is_available() else "cpu"
+model.to(device)
 
-# def generate_text(prompt, language):
-#     # Add language tag to prompt
-#     tagged_prompt = f"[{language.upper()}] {prompt}"
+def generate_text(prompt, language):
+    # Add language tag to prompt
+    tagged_prompt = f"[{language.upper()}] {prompt}"
     
-#     # Tokenize
-#     inputs = tokenizer(tagged_prompt, return_tensors="pt").to(device)
+    # Tokenize
+    inputs = tokenizer(tagged_prompt, return_tensors="pt").to(device)
     
-#     # Generate
-#     outputs = model.generate(
-#         **inputs,
-#         max_length=100,
-#         num_return_sequences=1,
-#         temperature=0.7,
-#         pad_token_id=tokenizer.eos_token_id
-#     )
+    # Generate
+    outputs = model.generate(
+        **inputs,
+        max_length=100,
+        num_return_sequences=1,
+        temperature=0.7,
+        pad_token_id=tokenizer.eos_token_id
+    )
     
-#     # Decode and return
-#     return tokenizer.decode(outputs[0], skip_special_tokens=True)
+    # Decode and return
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
 
-# # Create Gradio interface
-# iface = gr.Interface(
-#     fn=generate_text,
-#     inputs=[
-#         gr.Textbox(label="Enter your prompt"),
-#         gr.Dropdown(choices=["YORUBA", "IGBO", "HAUSA"], label="Select Language")
-#     ],
-#     outputs=gr.Textbox(label="Generated Text"),
-#     title="Nigerian Language Generator",
-#     description="Generate text in Yoruba, Igbo, or Hausa using a fine-tuned GPT model."
-# )
+# Create Gradio interface
+iface = gr.Interface(
+    fn=generate_text,
+    inputs=[
+        gr.Textbox(label="Enter your prompt"),
+        gr.Dropdown(choices=["YORUBA", "IGBO", "HAUSA"], label="Select Language")
+    ],
+    outputs=gr.Textbox(label="Generated Text"),
+    title="Nigerian Language Generator",
+    description="Generate text in Yoruba, Igbo, or Hausa using a fine-tuned GPT model."
+)
 
-# if __name__ == "__main__":
-#     iface.launch()
+if __name__ == "__main__":
+    iface.launch()
 
 
-import sys
-import os
-sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+# import sys
+# import os
+# sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) 
 
-from model.config import ModelConfig
-from model.model import NigerianLanguageModel
-from interface.gradio_app import create_interface
+# from model.config import ModelConfig
+# from model.model import NigerianLanguageModel
+# from interface.gradio_app import create_interface
 
-def main():
-    config = ModelConfig()
-    model = NigerianLanguageModel(config)
-    interface = create_interface(model)
-    interface.launch()
+# def main():
+#     config = ModelConfig()
+#     model = NigerianLanguageModel(config)
+#     interface = create_interface(model)
+#     interface.launch()
 
-if __name__ == "__main__":
-    main()
+# if __name__ == "__main__":
+#     main()