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That model was trained in part using their unreleased R1 "thinking" model. Today they've released R1 itself, together with a whole family of brand-new designs obtained from that base.

There's a great deal of things in the new release.

DeepSeek-R1-Zero seems the base design. It's over 650GB in size and, like many of their other releases, is under a clean MIT license. DeepSeek alert that "DeepSeek-R1-Zero experiences obstacles such as endless repetition, poor readability, and language mixing." ... so they also launched:

DeepSeek-R1-which "includes cold-start data before RL" and "attains efficiency comparable to OpenAI-o1 throughout mathematics, code, and reasoning jobs". That one is likewise MIT accredited, rca.co.id and is a comparable size.

I do not have the ability to run designs bigger than about 50GB (I have an M2 with 64GB of RAM), so neither of these two models are something I can quickly play with myself. That's where the new distilled designs are available in.

To support the research study neighborhood, drapia.org we have open-sourced DeepSeek-R1-Zero, DeepSeek-R1, and six dense designs distilled from DeepSeek-R1 based upon Llama and Qwen.

This is a remarkable flex! They have designs based on Qwen 2.5 (14B, 32B, Math 1.5 B and Math 7B) and Llama 3 (Llama-3.1 8B and Llama 3.3 70B Instruct).

Weirdly those Llama models have an MIT license connected, which I'm uncertain works with the underlying Llama license. Qwen designs are Apache certified so perhaps MIT is OK?

(I likewise simply observed the MIT license files say "Copyright (c) 2023 DeepSeek" so they may require to pay a little bit more attention to how they copied those in.)

Licensing aside, these distilled models are interesting beasts.

Running DeepSeek-R1-Distill-Llama-8B-GGUF

Quantized variations are currently starting to appear. Up until now I've tried just among those- unsloth/DeepSeek-R 1-Distill-Llama-8B-GGUF launched by Unsloth AI-and it's truly enjoyable to have fun with.

I'm running it using the combination of Ollama, LLM and setiathome.berkeley.edu the llm-ollama plugin.

First I brought and ran the design utilizing Ollama itself:

This downloads around 8.5 GB of model data and begins an interactive chat user .

Once the design has been brought, LLM can speak with it too. I choose utilizing LLM for experiments due to the fact that it logs whatever to SQLite for later exploration.

I set up the plugin and ran it like this:

Each reaction starts with a ... pseudo-XML tag containing the chain of idea utilized to assist create the response. For "a joke about a pelican and a walrus who run a tea space together" that began like this:

Okay, so I require to come up with a joke about a pelican and a walrus running a tea space together. Hmm, that's an interesting mix. Let me think of how these 2 characters might communicate in an amusing situation.

First, let's consider their attributes. Pelicans are understood for their long beaks and Webbed feet, wiki.tld-wars.space often seen near the beach or water. Walruses have huge teeth, thick fur, and they're generally found in cooler climates, like icebergs or snowy areas. So, integrating these 2 into a tea room setting is currently an amusing image.

[...]
It then believed for kenpoguy.com 20 paragraphs before outputting the joke! Here's the complete transcript and here's the output at the end, after the tag:

The Joke:

A pelican and a walrus decide to open a quaint little tea room together. The walrus, with its big size, struggles to find comfortable chairs, so it rests on the table by accident, knocking over the teapot. Meanwhile, the pelican, attempting to help, utilizes its beak to position saucers on the table, causing a couple of spills.

After a series of humorous mishaps, the walrus looks up and says with a smile, "This isn't so fishy anymore." The pelican smirks and remarks, "Maybe not, however we do have a lot of krill in our tea!"

Explanation:

- Setup: Pelican and Walrus run a not likely tea room. Their sizes lead to comical mayhem.

• Punchline: "This isn't so fishy anymore" is a pun on the circumstance becoming less unreasonable. The follow-up joke presents "krill," a play on words that connects into both marine life ("fish") and larsaluarna.se tea, making it amusing while fitting the style.
  
  So yeah, the joke is dreadful. But the process of getting there was such an interesting insight into how these brand-new models work.
  
  This was a fairly little 8B design. I'm eagerly anticipating trying out the Llama 70B variation, which isn't yet available in a GGUF I can keep up Ollama. Given the strength of Llama 3.3 70B-currently my favourite GPT-4 class design that I have actually run on my own machine-I have high expectations.
  
  Update 21st January 2025: I got this quantized variation of that Llama 3.3 70B R1 distilled design working like this-a 34GB download:
  
  Can it draw a pelican?
  
  I attempted my classic Generate an SVG of a pelican riding a bike prompt too. It did refrain from doing extremely well:
  
  It aimed to me like it got the order of the elements wrong, so I followed up with:
  
  the background wound up covering the remainder of the image
  
  It believed some more and gave me this:
  
  Just like the earlier joke, the chain of thought in the records was even more intriguing than completion outcome.
  
  Other methods to try DeepSeek-R1
  
  If you wish to try the model out without setting up anything at all you can do so utilizing chat.deepseek.com-you'll need to create an account (indication in with Google, use an email address or offer a Chinese +86 telephone number) and then select the "DeepThink" choice below the prompt input box.
  
  DeepSeek use the design via their API, utilizing an OpenAI-imitating endpoint. You can access that through LLM by dropping this into your extra-openai-models. yaml configuration file:
  
  Then run llm keys set deepseek and paste in your API secret, then use llm -m deepseek-reasoner 'timely' to run prompts.
  
  This will not show you the thinking tokens, regretfully. Those are served up by the API (example here) but LLM does not yet have a way to show them.