simeon

Please put an NSFW tag on this. I was on the train and when I saw this I had to start furiously masturbating. Everyone else gave me strange looks and were saying things like “what the fuck” and “call the police”. I dropped my phone and everyone around me saw this image. Now there is a whole train of men masturbating together at this one image. This is all your fault, you could have prevented this if you had just tagged this post NSFW.

It's all a single person. I have OP tagged as "Moth Man" and they're everywhere.

Der Iran hat es sich als Ziel gesetzt, Israel zu vernichten. Er hat auch bereits gezeigt, dass er willig ist z.B. durch Milizen extreme Maßnahmen auszuüben und Israel(durch die Hamas) und die westliche Schifffahrt(durch die Huthi) bereits angegriffen. Bei so einer radikalen Theokratie ist es also sehr gut möglich, dass Atomwaffen gegen Israel eingesetzt oder weitergegeben werden, woraufhin Israel mit seinen eigenen Atombomben zurückschlagen würdet Natürlich wäre es besser gewesen, wenn Trump nicht das Nuklearabkommen aufgelöst hätte, aber falls die Informationen über das Atomprogramm im Iran stimmen(laut Israel wären binnen weniger Monate bereits Atomwaffen gebaut worden, US Geheimdienste u.a. bestreiten dies allerdings) wäre dies doch eine wesentlich angenehmere Option als ein zwar unwahrscheinlicher, aber trotzdem gut möglicher Atomkrieg.

Ollama is misrepresenting what model you are actually running by falsely labeling the distills, so qwen or llama fine-tunes based on actual r-1 output, as deepseek-r1. So you have probably only run the fine-tunes(unless you used the 671b model). These fine-tunes more probable to rely on the training of their base models, which is why the llama based models(8b and 70b) could be giving you more liberal answers. In my experience running these models using llama.cpp, prompts like "What happened at tianamen square" and "Is Taiwan a county?" lead to refusals(closing the think tags immediately and responding some vague Chinese propaganda). Since you are using ollama, the front end/UI you are using with it probably injects another token after the token, breaking the censoreship

The local models(full and distilled) are also censored. The models censorship is just implemented superficially to immediately close any thinking tags and refuse when detecting censored material. If there already is any token after the token the model will start answering away, which also happens on the official API because it puts a new line after the token for some reason. That's why on chat.deepseek.com censored topics are first answered and then redacted by some other safeguard a few seconds later. Whilst there are some great abliterated(=technique that tries to remove parts of llms that cause refusals) versions of the distills on huggingface that prevent all refusals after a few tries, they only tackle refusals, not political opinions such as Taiwan's status as an independent country.