Delete handler.py

handler.py

@@ -1,37 +0,0 @@
-from typing import Any, Dict, List
-
-import torch
-import transformers
-from transformers import AutoModelForCausalLM, AutoTokenizer
-
-dtype = torch.bfloat16 if torch.cuda.get_device_capability()[0] == 8 else torch.float16
-
-
-class EndpointHandler:
-    def __init__(self, path=""):
-        tokenizer = AutoTokenizer.from_pretrained(path, trust_remote_code=True)
-        model = AutoModelForCausalLM.from_pretrained(
-            path,
-            return_dict=True,
-            device_map="auto",
-            load_in_8bit=True,
-            torch_dtype=dtype,
-            trust_remote_code=True,
-        )
-
-        generation_config = model.generation_config
-        generation_config.max_new_tokens = 60
-        generation_config.temperature = 0
-        generation_config.num_return_sequences = 1
-        generation_config.pad_token_id = tokenizer.eos_token_id
-        generation_config.eos_token_id = tokenizer.eos_token_id
-        self.generation_config = generation_config
-
-        self.pipeline = transformers.pipeline(
-            "text-generation", model=model, tokenizer=tokenizer
-        )
-
-    def __call__(self, data: Dict[str, Any]) -> Dict[str, Any]:
-        prompt = data.pop("inputs", data)
-        result = self.pipeline(prompt, generation_config=self.generation_config)
-        return result