Update app.py

app.py

@@ -6,8 +6,7 @@ from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStream
 import os
 from threading import Thread
 
-HF_TOKEN = os.environ.get("HF_TOKEN", None)
-MODEL_ID = "Nechba/Coin-Generative-Recognition"
+MODEL_ID = "THUDM/glm-4v-9b"
 
 TITLE = f'<br><center>🚀 Coin Generative Recognition</a></center>'
 
@@ -38,18 +37,15 @@ img {
     max-height: 300px; /* Limit the height of images */
 }
 """
-import os
-# Directory where the model and tokenizer will be saved
 
 # Load model directly
-from transformers import AutoModel
-model = AutoModel.from_pretrained("Nechba/Coin-Generative-Recognition", trust_remote_code=True).to(0)
-# model = AutoModelForCausalLM.from_pretrained(
-#     MODEL_ID,
-#     torch_dtype=torch.bfloat16,
-#     low_cpu_mem_usage=True,
-#     trust_remote_code=True
-# ).to(0)
+
+model = AutoModelForCausalLM.from_pretrained(
+    MODEL_ID,
+    torch_dtype=torch.bfloat16,
+    low_cpu_mem_usage=True,
+    trust_remote_code=True
+).to(0)
 
 tokenizer = AutoTokenizer.from_pretrained(MODEL_ID, trust_remote_code=True)
 model.eval()