change ckpt.pt path

handler.py

@@ -1,11 +1,16 @@
 from typing import Dict, List, Any
 import pipeline
+import gdown
 
 class EndpointHandler():
     def __init__(self, path=""):
         # Preload all the elements you are going to need at inference.
         # pseudo:
-        a = 1
+        file_name = 'ckpt.pt'
+        url = 'https://drive.google.com/file/d/1jt5zyFcyVUOd5kC_yMrcj3Wqk7kAzuPU/view?usp=sharing'
+        gdown.download(url, file_name, quiet=False)
+
+
 
     def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
         """

pipeline.py

@@ -4,6 +4,7 @@ import torch
 import tiktoken
 from model import GPTConfig, GPT
 
+
 init_from = 'resume'  # either 'resume' (from an out_dir) or a gpt2 variant (e.g. 'gpt2-xl')
 out_dir = 'out-stinfo'  # ignored if init_from is not 'resume'
 start = "\n"  # or "<|endoftext|>" or etc. Can also specify a file, use as: "FILE:prompt.txt"
@@ -29,7 +30,8 @@ def infer():
     ctx = nullcontext() if device_type == 'cpu' else torch.amp.autocast(
         device_type=device_type, dtype=ptdtype)
 
-    ckpt_path = os.path.join(os.getcwd(), out_dir, 'ckpt.pt')
+    # ckpt_path = os.path.join(os.getcwd(), out_dir, 'ckpt.pt')
+    ckpt_path = 'ckpt.pt'
     checkpoint = torch.load(ckpt_path, map_location=device)
     gptconf = GPTConfig(**checkpoint['model_args'])
     model = GPT(gptconf)

requirements.txt

@@ -2,3 +2,4 @@
 torch
 tiktoken
 numpy
+gdown