Upload handler.py

handler.py

@@ -0,0 +1,30 @@
+import llama
+from typing import Dict, List, Any
+
+MODEL = 'decapoda-research/llama-7b-hf'
+
+
+# MODEL = 'decapoda-research/llama-13b-hf'
+# MODEL = 'decapoda-research/llama-30b-hf'
+# MODEL = 'decapoda-research/llama-65b-hf'
+
+class EndpointHandler():
+    def __init__(self, path=""):
+        self.tokenizer = llama.LLaMATokenizer.from_pretrained(MODEL)
+        self.model = llama.LLaMAForCausalLM.from_pretrained(MODEL, low_cpu_mem_usage=True, load_in_8bit=True)
+        self.model.to('cuda')
+
+    def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
+        inputs = data.pop("inputs", data)
+        parameters = data.pop("parameters", None)
+
+        input_ids = self.tokenizer(inputs, return_tensors="pt", add_special_tokens=False).input_ids.cuda()
+
+        if parameters is not None:
+            outputs = self.model.generate(input_ids, **parameters)
+        else:
+            outputs = self.model.generate(input_ids)
+
+        prediction = self.tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+        return [{"generated_text": prediction}]