Update README.md

README.md

@@ -17,29 +17,34 @@ import transformers
 from optimum.intel.openvino import OVModelForCausalLM
 import torch
 import os
+from huggingface_hub import create_repo, upload_folder
 
 source_model_id = 'tiiuae/falcon-7b'
 save_path = '/tmp/yujiepan/falcon-tiny-random'
 repo_id = 'yujiepan/falcon-tiny-random'
 
-config = transformers.AutoConfig.from_pretrained(source_model_id, trust_remote_code=True)
+config = transformers.AutoConfig.from_pretrained(
+    source_model_id, trust_remote_code=True)
 config.hidden_size = 8
 config.n_head = 2
 config.n_layer = 2
-config.torch_dtype = 'float16'
+config.torch_dtype = torch.float16
 
-model = transformers.AutoModelForCausalLM.from_config(config,trust_remote_code=True)
+model = transformers.AutoModelForCausalLM.from_config(
+    config, trust_remote_code=True)
+model = model.half()
 model.save_pretrained(save_path)
 
-tokenizer = transformers.AutoTokenizer.from_pretrained(source_model_id, trust_remote_code=True)
+tokenizer = transformers.AutoTokenizer.from_pretrained(
+    source_model_id, trust_remote_code=True)
 tokenizer.save_pretrained(save_path)
 
 # current not supported, might add this later
-# ovmodel = OVModelForCausalLM.from_pretrained(save_path, export=True, trust_remote_code=True)
+# ovmodel = OVModelForCausalLM.from_pretrained(
+#     save_path, export=True, trust_remote_code=True)
 # ovmodel.save_pretrained(save_path)
 
 os.system(f'ls -alh {save_path}')
-from huggingface_hub import create_repo, upload_folder
 create_repo(repo_id, exist_ok=True)
 upload_folder(repo_id=repo_id, folder_path=save_path)
 ```