In the realm of Language Model (LM) applications, determinism plays a crucial role, especially when consistent and predictable outcomes are desired.
temperature=0
essentially turns off randomness, leading the model to choose the most likely next word at each step. This is critical for achieving determinism as it minimizes variance in the model’s output.
temperature=0
, offers an even higher degree of predictability.
temperature=0
to reduce randomness but without the added predictability that seed offers.
Sometimes, determinism may be impacted due to necessary changes OpenAI makes to model configurations on our end. To help you keep track of these changes, we expose the system_fingerprint field. If this value is different, you may see different outputs due to changes we’ve made on our systems.
temperature=0
for reducing randomness. Stay tuned for future updates as we work towards integrating seed functionality with AzureOpenAI.
For OpenAI Users: Utilize both temperature=0
and seed for maximum determinism.