Create app.py

app.py

@@ -0,0 +1,30 @@
+from transformers import AutoModelForCausalLM, AutoTokenizer
+device = "cuda" # the device to load the model onto
+
+model = AutoModelForCausalLM.from_pretrained(
+    "NTQAI/Nxcode-CQ-7B-orpo",
+    torch_dtype="auto",
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained("NTQAI/Nxcode-CQ-7B-orpo")
+
+prompt = """Complete the following Python function:
+from typing import List
+
+
+def has_close_elements(numbers: List[float], threshold: float) -> bool:
+    """ Check if in given list of numbers, are any two numbers closer to each other than
+    given threshold.
+    >>> has_close_elements([1.0, 2.0, 3.0], 0.5)
+    False
+    >>> has_close_elements([1.0, 2.8, 3.0, 4.0, 5.0, 2.0], 0.3)
+    True
+    """
+"""
+messages = [
+    {"role": "user", "content": prompt}
+]
+
+inputs = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device)
+outputs = model.generate(inputs, max_new_tokens=512, do_sample=False, top_k=50, top_p=0.95, num_return_sequences=1, eos_token_id=tokenizer.eos_token_id)
+res = tokenizer.decode(outputs[0][len(inputs[0]):], skip_special_tokens=True)