点击领取

import osimport jsonimport tqdmimport openaifrom time import sleepfrom pathlib import Path
chat_models = ["gpt-4", "gpt-3.5-turbo"]message_history = [    {"role": "system", "content": "You are a helpful assistant."},    {"role": "user", "content": "Write a unique, surprising, extremely randomized story with highly unpredictable changes of events."}]
completion_models = ["text-davinci-003", "text-davinci-001", "davinci-instruct-beta", "davinci"]prompt = "[System: You are a helpful assistant]\n\nUser: Write a unique, surprising, extremely randomized story with highly unpredictable changes of events.\n\nAI:"
results = []
import timeclass TimeIt:    def __init__(self, name): self.name = name    def __enter__(self): self.start = time.time()    def __exit__(self, *args): print(f"{self.name} took {time.time() - self.start} seconds")
C = 30  # number of completions to make per modelN = 128 # max_tokens# Testing chat modelsfor model in chat_models:    sequences = set()    errors = 0 # although I track errors, at no point were any errors ever emitted    with TimeIt(model):        for _ in range(C):            try:                completion = openai.ChatCompletion.create(                    model=model,                    messages=message_history,                    max_tokens=N,                    temperature=0,                    logit_bias={"100257": -100.0}, # this doesn't really do anything, because chat models don't do <|endoftext|> much                )                sequences.add(completion.choices[0].message['content'])                sleep(1) # cheaply avoid rate limiting            except Exception as e:                print('something went wrong for', model, e)                errors += 1    print(f"\nModel {model} created {len(sequences)} ({errors=}) unique sequences:")    print(json.dumps(list(sequences)))    results.append((len(sequences), model))# Testing completion modelsfor model in completion_models:    sequences = set()    errors = 0    with TimeIt(model):        for _ in range(C):            try:                completion = openai.Completion.create(                    model=model,                    prompt=prompt,                    max_tokens=N,                    temperature=0,                    logit_bias = {"50256": -100.0}, # prevent EOS                )                sequences.add(completion.choices[0].text)                sleep(1)            except Exception as e:                print('something went wrong for', model, e)                errors += 1    print(f"\nModel {model} created {len(sequences)} ({errors=}) unique sequences:")    print(json.dumps(list(sequences)))    results.append((len(sequences), model))
# Printing table of resultsprint("\nTable of Results:")print("Num_Sequences\tModel_Name")for num_sequences, model_name in results:    print(f"{num_sequences}\t{model_name}")