Upload app.py

app.py

@@ -158,7 +158,8 @@ emotion_classifier = hf_pipeline("text-classification", model="nateraw/bert-base
 
 device = 0 if torch.cuda.is_available() else -1
 tokenizer = AutoTokenizer.from_pretrained(READER_MODEL_NAME)
-model = AutoModelForCausalLM.from_pretrained(READER_MODEL_NAME).to(device)
+model = AutoModelForCausalLM.from_pretrained(READER_MODEL_NAME)
+#model = AutoModelForCausalLM.from_pretrained(READER_MODEL_NAME).to(device)
 READER_LLM = pipeline(
     model=model,
     tokenizer=tokenizer,
@@ -168,7 +169,7 @@ READER_LLM = pipeline(
     repetition_penalty=1.1,
     return_full_text=False,
     max_new_tokens=500,
-    device=device,
+#    device=device,
 )
 # -------------------------------
 # 🔧 Whisper Model Setup