Create proxy_model.py

proxy_model.py

@@ -0,0 +1,27 @@
+import os
+import requests
+import torch
+from transformers import AutoTokenizer, AutoConfig, AutoModelForCausalLM
+
+class RemoteModelProxy:
+    def __init__(self, model_id):
+        self.model_id = model_id
+        self.tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+        self.config = AutoConfig.from_pretrained(model_id, trust_remote_code=True)
+        self.model = AutoModelForCausalLM.from_pretrained(model_id, config=self.config, trust_remote_code=True)
+
+    def classify_text(self, text):
+        inputs = self.tokenizer(text, return_tensors="pt", padding=True, truncation=True)
+        logits = self.model(**inputs)
+        probabilities = torch.softmax(logits, dim=-1).tolist()[0]
+        predicted_class = torch.argmax(logits, dim=-1).item()
+        return {
+            "Predicted Class": predicted_class,
+            "Probabilities": probabilities
+        }
+
+if __name__ == "__main__":
+    model_id = "deepseek-ai/DeepSeek-V3"
+    proxy = RemoteModelProxy(model_id)
+    result = proxy.classify_text("Your input text here")
+    print(result)