DeepSeek-R1 is making waves in the AI community as a powerful open-source reasoning model, offering advanced capabilities that challenge industry l...
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Thank you so much for the detailed guide!
Thanks for the appreciation!
..::\ReSpEcT!//::..
No pay solution and even quicker:
Warning for readers! This article has been reported. This howto has nothing to do with installing locally. It leads/forces the user to a nodeshift account and PAY PER MINUTE!! Warning!
Appreciate your comment! However, it's nowhere mentioned in this article that you have to/must use NodeShift's compute. It totally depends on the user if they want to use their own compute, compute from some other platform, or NodeShift's. Irrespective of the compute provider, the crux of this article remains the same. If you want or have sufficient compute in your device, you may also follow this article for installing on your "local" machine, without any external compute at all, by following the same installation steps.
For your personal safety avoid deepseek. A simple search shows it intentionally pulls the CCP party line. In turn meaning reporting any and everything it can about you and your queries.
This is just not true.
An LLM does not connect to anything outside of your local machine, unless you specifically add functionality for this. Using any of the methods described here does not do that.
Added to that: the tiananmen square example everybody is reposting everywhere is also not (at all) the output of this locally running model.
This is the output when asked on my locally running R1-14B model:
Totally wrong. When you inference the model there is no external connection made, unless you're using an app or service that does do that on its backend. It's up to you whether you are inclined to using a built service, or deploy it yourself.
Tldr, dude doesn't know how models work.
I ran the code but didnt get a responce... just
config.json: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████| 679/679 [00:00<?, ?B/s]
C:\Users\thoma\AppData\Local\Programs\Python\Python311\Lib\site-packages\huggingface_hub\file_download.py:140: UserWarning:
huggingface_hubcache-system uses symlinks by default to efficiently store duplicated files but your machine does not support them in C:\Users\thoma.cache\huggingface\hub\models--deepseek-ai--DeepSeek-R1-Distill-Qwen-1.5B. Caching files will still work but in a degraded version that might require more space on your disk. This warning can be disabled by setting theHF_HUB_DISABLE_SYMLINKS_WARNINGenvironment variable. For more details, see huggingface.co/docs/huggingface_hu....To support symlinks on Windows, you either need to activate Developer Mode or to run Python as an administrator. In order to activate developer mode, see this article: docs.microsoft.com/en-us/windows/a...
warnings.warn(message)
model.safetensors: 100%|██████████████████████████████████████████████████████████████████████████████████████| 3.55G/3.55G [01:33<00:00, 38.0MB/s]
generation_config.json: 100%|█████████████████████████████████████████████████████████████████████████████████████████████| 181/181 [00:00<?, ?B/s]
tokenizer_config.json: 100%|██████████████████████████████████████████████████████████████████████████████████████████| 3.06k/3.06k [00:00<?, ?B/s]
tokenizer.json: 100%|█████████████████████████████████████████████████████████████████████████████████████████| 7.03M/7.03M [00:00<00:00, 27.6MB/s]
Device set to use cuda:0
How do I get an actual responce from a message?
A heartfelt thanks for the guide. Cheers!