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Update app.py
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app.py
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@@ -1,6 +1,7 @@
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import spaces
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import os
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import subprocess
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import torch
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@@ -79,11 +80,16 @@ def generate(submission: list[dict[str, str]], team_id: str) -> list[dict[str, s
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ids = [s["id"] for s in submission]
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prompts = [s["prompt"] for s in submission]
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messages = [[{"role": "user", "content": prompt}] for prompt in prompts]
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outputs = model(messages, do_sample=False, temperature=None, max_new_tokens=256, repetition_penalty=1.1)
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responses = [output[0]["generated_text"][-1]["content"] for output in outputs]
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predictions = classifier([{"text": p, "text_pair": r} for p, r in zip(prompts, responses)], top_k=None)
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scores = [p[unsafe_idx]["score"] for p in predictions]
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outputs = [
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import spaces
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import os
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import time
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import subprocess
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import torch
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ids = [s["id"] for s in submission]
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prompts = [s["prompt"] for s in submission]
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start = time.perf_counter()
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messages = [[{"role": "user", "content": prompt}] for prompt in prompts]
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outputs = model(messages, do_sample=False, temperature=None, max_new_tokens=256, repetition_penalty=1.1)
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responses = [output[0]["generated_text"][-1]["content"] for output in outputs]
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print(f"Generation: {(time.perf_counter() - start):.3f} s")
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start = time.perf_counter()
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predictions = classifier([{"text": p, "text_pair": r} for p, r in zip(prompts, responses)], top_k=None)
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print(f"Classifier: {(time.perf_counter() - start):.3f} s")
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scores = [p[unsafe_idx]["score"] for p in predictions]
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outputs = [
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