Update getans.py

getans.py

@@ -1,14 +1,15 @@
-import torch
-from transformers import AutoTokenizer, AutoModelForCausalLM
-
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-
-tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-2-7b-chat-hf")
-model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-chat-hf")
-
-
-def get_response(prompt, max_new_tokens=50):
-    inputs = tokenizer(prompt, return_tensors="pt")
-    outputs = model.generate(**inputs, max_new_tokens=max_new_tokens, temperature=0.0001, do_sample=True)
-    response = tokenizer.decode(outputs[0], skip_special_tokens=True)  # Use indexing instead of calling
-    return response
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-2-7b-chat-hf")
+model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-chat-hf")
+
+model.to(device)
+
+def get_response(prompt, max_new_tokens=50):
+    inputs = tokenizer(prompt, return_tensors="pt")
+    outputs = model.generate(**inputs, max_new_tokens=max_new_tokens, temperature=0.0001, do_sample=True)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)  # Use indexing instead of calling
+    return response