That model was trained in part using their unreleased R1 "thinking" model. Today they have actually launched R1 itself, along with a whole household of new designs obtained from that base.

There's an entire lot of stuff 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 challenges such as limitless repetition, bad readability, and language blending." ... so they also launched:

DeepSeek-R1-which "incorporates cold-start data before RL" and "attains efficiency equivalent to OpenAI-o1 throughout mathematics, code, and thinking jobs". That a person is also MIT licensed, and is a comparable size.

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

To support the research study neighborhood, we have open-sourced DeepSeek-R1-Zero, DeepSeek-R1, and 6 thick models distilled from DeepSeek-R1 based upon Llama and Qwen.

This is a remarkable flex! They have 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 designs have an MIT license attached, which I'm uncertain works with the underlying Llama license. Qwen models are Apache certified so maybe MIT is OK?

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

Licensing aside, these distilled models are fascinating beasts.

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

Quantized variations are currently beginning to appear. So far I've tried simply among those- unsloth/DeepSeek-R 1-Distill-Llama-8B-GGUF launched by Unsloth AI-and it's actually fun to have fun with.

I'm running it utilizing the combination of Ollama, LLM and the llm-ollama plugin.

First I brought and ran the model utilizing Ollama itself:

This downloads around 8.5 GB of model data and starts an interactive chat interface.

Once the design has actually been fetched, suvenir51.ru LLM can talk to it also. I prefer using LLM for experiments because it logs whatever to SQLite for later expedition.

I installed the plugin and ran it like this:

Each response starts with a ... pseudo-XML tag containing the chain of thought utilized to help produce the reaction. For "a joke about a pelican and a walrus who run a tea room together" that started like this:

Okay, so I need to come up with a joke about a pelican and a walrus running a tea space together. Hmm, that's an interesting combination. Let me think of how these two characters may communicate in a humorous circumstance.

First, let's consider their attributes. Pelicans are understood for their long beaks and Webbed feet, often seen near the beach or water. Walruses have big teeth, thick fur, and they're generally found in chillier climates, like icebergs or snowy locations. So, combining these 2 into a tea room setting is currently a funny image.

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

The Joke:

A pelican and a walrus choose to open a quaint little tea space together. The walrus, with its huge size, has a hard time to find comfortable chairs, so it sits on the table by mishap, knocking over the teapot. Meanwhile, the pelican, trying to assist, utilizes its beak to place dishes on the table, causing a couple of spills.

After a series of humorous incidents, the walrus searches for and states with a grin, "This isn't so fishy anymore." The pelican smirks and mentions, "Maybe not, however we do have a lot of krill in our tea!"

Explanation:

- Setup: Pelican and Walrus run a not likely tea space. Their sizes result in comical turmoil.

• Punchline: "This isn't so fishy anymore" is a pun on the circumstance ending up being less ridiculous. The follow-up joke presents "krill," a play on words that connects into both marine life ("fish") and tea, making it funny while fitting the theme.
  
  So yeah, the joke is awful. But the procedure of getting there was such an intriguing insight into how these brand-new designs work.
  
  This was a fairly little 8B design. I'm eagerly anticipating checking 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 preferred GPT-4 class design that I've operated on my own machine-I have high expectations.
  
  Update 21st January 2025: I got this quantized version of that Llama 3.3 70B R1 distilled design working like this-a 34GB download:
  
  Can it draw a pelican?
  
  I tried my traditional 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 components incorrect, koha-community.cz so I followed up with:
  
  the background ended up covering the remainder of the image
  
  It believed some more and offered me this:
  
  Just like the earlier joke, the chain of thought in the records was much more fascinating than the end result.
  
  Other methods to attempt DeepSeek-R1
  
  If you wish to attempt the design out without installing anything you can do so utilizing chat.deepseek.com-you'll need to produce an account (check in with Google, utilize an email address or provide a Chinese +86 phone number) and after that select the "DeepThink" alternative below the timely input box.
  
  DeepSeek use the model by means of their API, using an OpenAI-imitating endpoint. You can access that through LLM by dropping this into your extra-openai-models. yaml setup file:
  
  Then run llm keys set deepseek and paste in your API key, then use llm -m deepseek-reasoner 'prompt' to run prompts.
  
  This will not reveal you the thinking tokens, unfortunately. Those are served up by the API (example here) however LLM doesn't yet have a method to show them.