Messing with configuration.

app.py

@@ -20,8 +20,8 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
-print(f"Is CUDA available: {torch.cuda.is_available()}")
-print(f"CUDA device: {torch.cuda.get_device_name(torch.cuda.current_device())}")
+# print(f"Is CUDA available: {torch.cuda.is_available()}")
+# print(f"CUDA device: {torch.cuda.get_device_name(torch.cuda.current_device())}")
 
 # "xenova/mobilebert-uncased-mnli" "typeform/mobilebert-uncased-mnli" Fast but small--same as bundled in Statosphere
 # "xenova/deberta-v3-base-tasksource-nli" Not impressed
@@ -37,6 +37,7 @@ tokenizer_name = "MoritzLaurer/deberta-v3-base-zeroshot-v2.0"
 # model = ORTModelForSequenceClassification.from_pretrained(model_name, export=True, provider="CUDAExecutionProvider")
 # tokenizer = AutoTokenizer.from_pretrained(tokenizer_name, model_max_length=512)
 
+# classifier = pipeline(task="zero-shot-classification", model=model_name, tokenizer=tokenizer_name)
 classifier = pipeline(task="zero-shot-classification", model=model_name, tokenizer=tokenizer_name, device="cuda:0")
 
 def classify(data_string, request: gradio.Request):

requirements.txt

@@ -3,5 +3,5 @@ fastapi==0.88.0
 huggingface_hub==0.26.0
 json5==0.9.25
 numpy
-optimum[onnxruntime-gpu]==1.24.0
+optimum[onnxruntime]==1.24.0
 transformers==4.36