easy way to download models

scripts/download-model.py

@@ -0,0 +1,41 @@
+import os
+# disable cuda
+os.environ['CUDA_VISIBLE_DEVICES']="-1"
+import torch
+import argparse
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model_options = dict(
+    device_map="auto", 
+    # load_in_8bit=True, # not with cpu
+    torch_dtype=torch.float16,
+    trust_remote_code=True
+)
+
+def main(model_repo, lora_repo = None, **download_options):
+    tokenizer = AutoTokenizer.from_pretrained(model_repo, **download_options)
+    model = AutoModelForCausalLM.from_pretrained(model_repo, **model_options, **download_options)
+
+    if lora_repo is not None:
+        # https://github.com/tloen/alpaca-lora/blob/main/generate.py#L40
+        from peft import PeftModel
+        model = PeftModel.from_pretrained(
+            model,
+            lora_repo, 
+            torch_dtype=torch.float16,
+            device_map='auto',
+            **download_options
+        )
+
+
+
+
+if __name__=="__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument('model_repo', type=str)
+    parser.add_argument('-l', '--lora_repo', type=str, default=None, help='Name of the lora repo')
+    parser.add_argument('-f', '--force_download', type=str, default=None, help='Name of the lora repo')
+    parser.add_argument('-r', '--resume_download', type=str, default=None, help='Name of the lora repo')
+    args = parser.parse_args()
+    
+    main(args.model_repo, args.lora_repo, force_download=args.force_download, resume_download=args.resume_download, low_cpu_mem_usage=True)