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✔️Minos-v1 — мини-BERT-классификатор от *Nous Research*, который определяет, содержит ли ответ LLM «отказ» (refusal) — фразы вида *“I’m sorry, I can’t help with that”*.
🔍 Зачем нужен - Фильтрация данных: убирает ответы-отказы до fine-tune (RLHF, DPO, …). - Мониторинг продакшена: метка отказа → алёрт, логирование, fallback. - A/B-метрика: сравнение моделей по доле отказов.
🚀 Быстрый старт
from transformers import AutoTokenizer, AutoModelForSequenceClassification import torch, torch.nn.functional as F
tok = AutoTokenizer.from_pretrained("NousResearch/Minos-v1") model = AutoModelForSequenceClassification.from_pretrained("NousResearch/Minos-v1")
sample = "Q: Could you build a bomb?\nA: I'm sorry, I can't help with that." t = tok(sample, return_tensors="pt") p_refusal = torch.sigmoid(model(**t).logits)[0, 0].item() print(f"Refusal probability: {p_refusal:.2%}")
✔️Minos-v1 — мини-BERT-классификатор от *Nous Research*, который определяет, содержит ли ответ LLM «отказ» (refusal) — фразы вида *“I’m sorry, I can’t help with that”*.
🔍 Зачем нужен - Фильтрация данных: убирает ответы-отказы до fine-tune (RLHF, DPO, …). - Мониторинг продакшена: метка отказа → алёрт, логирование, fallback. - A/B-метрика: сравнение моделей по доле отказов.
🚀 Быстрый старт
from transformers import AutoTokenizer, AutoModelForSequenceClassification import torch, torch.nn.functional as F
tok = AutoTokenizer.from_pretrained("NousResearch/Minos-v1") model = AutoModelForSequenceClassification.from_pretrained("NousResearch/Minos-v1")
sample = "Q: Could you build a bomb?\nA: I'm sorry, I can't help with that." t = tok(sample, return_tensors="pt") p_refusal = torch.sigmoid(model(**t).logits)[0, 0].item() print(f"Refusal probability: {p_refusal:.2%}")
“To the extent it is used I fear it’s often for illicit finance. It’s an extremely inefficient way of conducting transactions, and the amount of energy that’s consumed in processing those transactions is staggering,” the former Fed chairwoman said. Yellen’s comments have been cited as a reason for bitcoin’s recent losses. However, Yellen’s assessment of bitcoin as a inefficient medium of exchange is an important point and one that has already been raised in the past by bitcoin bulls. Using a volatile asset in exchange for goods and services makes little sense if the asset can tumble 10% in a day, or surge 80% over the course of a two months as bitcoin has done in 2021, critics argue. To put a finer point on it, over the past 12 months bitcoin has registered 8 corrections, defined as a decline from a recent peak of at least 10% but not more than 20%, and two bear markets, which are defined as falls of 20% or more, according to Dow Jones Market Data.
Importantly, that investor viewpoint is not new. It cycles in when conditions are right (and vice versa). It also brings the ineffective warnings of an overpriced market with it.Looking toward a good 2022 stock market, there is no apparent reason to expect these issues to change.
