Create app.py

app.py

@@ -0,0 +1,48 @@
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
+import torch
+from huggingface_hub import login
+
+def merge_model(hf_token):
+    try:
+        login(token=hf_token)
+        yield "✓ Logged in successfully\n"
+        
+        yield "Loading base model (this takes 2-3 min)...\n"
+        base_model = AutoModelForCausalLM.from_pretrained(
+            "HuggingFaceH4/zephyr-7b-beta",
+            torch_dtype=torch.float16,
+            device_map="auto",
+            low_cpu_mem_usage=True
+        )
+        yield "✓ Base model loaded\n"
+        
+        yield "Loading tokenizer...\n"
+        tokenizer = AutoTokenizer.from_pretrained("HuggingFaceH4/zephyr-7b-beta")
+        yield "✓ Tokenizer loaded\n"
+        
+        yield "Loading your adapter...\n"
+        model = PeftModel.from_pretrained(base_model, "youtiva-123/autotrain-r6w6w-7pv2i")
+        yield "✓ Adapter loaded\n"
+        
+        yield "Merging adapter with base model...\n"
+        merged_model = model.merge_and_unload()
+        yield "✓ Models merged\n"
+        
+        yield "Uploading to youtiva-123/zephyr-youtiva-merged...\n"
+        merged_model.push_to_hub("youtiva-123/zephyr-youtiva-merged")
+        tokenizer.push_to_hub("youtiva-123/zephyr-youtiva-merged")
+        
+        yield "✅ SUCCESS! Your merged model is ready at:\nhttps://huggingface.co/youtiva-123/zephyr-youtiva-merged\n\nNow go deploy this model as an endpoint!"
+    except Exception as e:
+        yield f"❌ Error: {str(e)}"
+
+interface = gr.Interface(
+    fn=merge_model,
+    inputs=gr.Textbox(label="Hugging Face Token (needs write access)", type="password"),
+    outputs=gr.Textbox(label="Status", lines=15),
+    title="Merge LoRA Adapter with Base Model"
+)
+
+interface.launch()