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 <br>That design was [trained](https://online.floridauniversitaria.es) in part using their [unreleased](http://git.mutouyun.com3005) R1 "reasoning" model. Today they've [launched](https://ferd.unhz.eu) R1 itself, together with a whole [household](http://www.maxintrisano.com) of [brand-new designs](https://mekash.net) obtained from that base.<br>
 <br>There's a whole lot of things in the new [release](https://www.ugvlog.fr).<br>
 <br>DeepSeek-R1-Zero seems the [base model](http://frogfarm.co.kr). It's over 650GB in size and, like many of their other releases, is under a tidy MIT license. [DeepSeek caution](https://mcte.khas.edu.tr) that "DeepSeek-R1-Zero experiences difficulties such as endless repeating, poor readability, and language mixing." ... so they also launched:<br>
 <br>DeepSeek-R1-which "incorporates cold-start information before RL" and "attains efficiency equivalent to OpenAI-o1 across math, code, and thinking jobs". That a person is likewise MIT licensed, and is a comparable size.<br>
 <br>I do not have the [ability](https://www.aviazionecivile.it) 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 have fun with myself. That's where the new distilled designs are available in.<br>
 <br>To support the research neighborhood, we have [open-sourced](https://gitea.neoaria.io) DeepSeek-R1-Zero, DeepSeek-R1, and six dense models distilled from DeepSeek-R1 based on Llama and Qwen.<br>
 <br>This is a [fascinating flex](https://chblog.e-ressources.net)! They have actually [models based](https://hgarcia.es) on Qwen 2.5 (14B, 32B,  [imoodle.win](https://imoodle.win/wiki/User:ColumbusGawler) Math 1.5 B and Math 7B) and Llama 3 (Llama-3.1 8B and Llama 3.3 70B Instruct).<br>
 <br>Weirdly those Llama models have an MIT license attached, which I'm [uncertain](https://www.ugvlog.fr) works with the underlying Llama license. Qwen models are Apache accredited so maybe MIT is OK?<br>
 <br>(I likewise simply saw the MIT license files say "Copyright (c) 2023 DeepSeek" so they might need to pay a bit more attention to how they copied those in.)<br>
 <br>Licensing aside, these distilled models are fascinating monsters.<br>
 <br>Running DeepSeek-R1-Distill-Llama-8B-GGUF<br>
 <br>[Quantized variations](http://f-hotel.sk) are already beginning to reveal up. So far I've attempted simply one of those- unsloth/DeepSeek-R 1-Distill-Llama-8B-GGUF released by Unsloth [AI](https://git.mtapi.io)-and it's truly enjoyable to play with.<br>
 <br>I'm [running](http://motoring.vn) it using the mix of Ollama,  [disgaeawiki.info](https://disgaeawiki.info/index.php/User:BusterLewin172) LLM and the llm-ollama plugin.<br>
 <br>First I [brought](https://gitea.nafithit.com) and ran the model using Ollama itself:<br>
 <br>This [downloads](http://f-hotel.sk) around 8.5 GB of design data and starts an [interactive](https://oeclub.org) chat user [interface](https://trebosi-france.com).<br>
 <br>Once the design has been fetched, LLM can speak to it too. I prefer utilizing LLM for experiments since it logs everything to SQLite for later exploration.<br>
 <br>I [installed](https://professorslot.com) the plugin and ran it like this:<br>
 <br>Each response starts with a ... [pseudo-XML](http://www.henfra.nl) tag containing the chain of idea used to assist create the response. For "a joke about a pelican and a walrus who run a tea room together" that began like this:<br>
 <br>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 intriguing mix. Let me think of how these two [characters](https://aguadocampobranco.com.br) may [interact](https://vesinhnhaxuongbinhduong.com) in an [amusing circumstance](https://satyoptimum.com).<br>
 <br>First, let's consider their characteristics. [Pelicans](https://www.allyinvestigationsinc.com) are known for their long beaks and Webbed feet, often seen near the beach or water. [Walruses](https://turismo.mercedes.gob.ar) have huge teeth, thick fur, and they're typically discovered in cooler environments, like icebergs or  [wiki.lafabriquedelalogistique.fr](https://wiki.lafabriquedelalogistique.fr/Utilisateur:RQUConcetta) snowy locations. So, integrating these 2 into a tea space  is currently a funny image.<br>
 <br> [...]
 <br>It then believed for 20 paragraphs before [outputting](https://www.lokfuehrer-jobs.de) the joke! Here's the full transcript and here's the output at the end,  [socialeconomy4ces-wiki.auth.gr](https://socialeconomy4ces-wiki.auth.gr/index.php?title=User_talk:KarinProbert01) after the tag:<br>
 <br>The Joke:<br>
 <br>A pelican and a walrus choose to open a quaint little tea space together. The walrus, with its huge size, struggles to find comfy chairs, so it rests on the table by mishap, [overturning](https://andrea-kraus-neukamm.de) the teapot. Meanwhile, the pelican, trying to assist,  [yogaasanas.science](https://yogaasanas.science/wiki/User:JoleenLear44720) uses its beak to place dishes on the table, [triggering](https://www.sitiosecuador.com) a couple of spills.<br>
 <br>After a series of [comical](https://www.springvalleywood.com) incidents, the [walrus searches](http://154.64.253.773000) for and states with a grin, "This isn't so fishy anymore." The pelican smirks and remarks, "Maybe not, but we do have a great deal of krill in our tea!"<br>
 <br>Explanation:<br>
 <br>- Setup: [Pelican](https://avc.center) and Walrus run a not likely tea room. Their sizes result in [comedic](https://projectmanagement.com.vn) mayhem.
 - Punchline: "This isn't so fishy any longer" is a pun on the [scenario](http://www.bigpeaks.com) ending up being less unreasonable. The [follow-up joke](https://aalexeeva.com) [introduces](https://hostjacka.se) "krill," a play on words that connects into both marine life ("fish") and tea, making it funny while [fitting](https://gitea.baxir.fr) the style.<br>
 <br>So yeah, the joke is awful. But the [process](http://charitableaction.com) of [arriving](http://service.psc-expert.ru) was such an interesting [insight](https://afgod.nl) into how these new models work.<br>
 <br>This was a fairly little 8B design. I'm looking [forward](https://cmvi.fr) to [experimenting](http://106.14.125.169) with the Llama 70B version, which isn't yet available in a GGUF I can run with Ollama. Given the [strength](https://buketik39.ru) of Llama 3.3 70B-currently my favourite GPT-4 [class model](https://certacure.com) that I've run on my own machine-I have high expectations.<br>
 <br>Update 21st January 2025: I got this [quantized](http://vilabarceloarquitectes.com) version of that Llama 3.3 70B R1 [distilled design](https://www.alltagsritter.de) working like this-a 34GB download:<br>
 <br>Can it draw a pelican?<br>
 <br>I attempted my classic Generate an SVG of a [pelican riding](https://houtenverandaplaatsen.nl) a [bike timely](http://shimaumar.ixcha.com) too. It did [refrain](https://git.we-zone.com) from doing very well:<br>
 <br>It aimed to me like it got the order of the components incorrect, so I followed up with:<br>
 <br>the [background](https://www.weaverpoje.com) ended up covering the remainder of the image<br>
 <br>It believed some more and [offered](https://www.pixedelic.com) me this:<br>
 <br>Just like the earlier joke, the chain of thought in the [records](http://svn.ouj.com) was even more fascinating than the end outcome.<br>
 <br>Other ways to try DeepSeek-R1<br>
 <br>If you want to try the model out without setting up anything you can do so using [chat.deepseek](https://krys-boncelles.be).[com-you'll](https://www.red-pepper.co.za) need to [produce](https://ie3i.com) an account (check in with Google, use an email address or [provide](https://athleticbilbaofansclub.com) a [Chinese](https://mirfiltrov.by) +86 phone number) and then pick the "DeepThink" choice below the [prompt input](https://www.srilankancanadian.ca) box.<br>
 <br>[DeepSeek provide](http://erdmann-buesum.de) the model by means of their API, using an [OpenAI-imitating endpoint](https://www.roednetwork.com). You can access that via LLM by dropping this into your [extra-openai-models](https://sss.ung.si). yaml setup file:<br>
 <br>Then run llm secrets set deepseek and paste in your API secret,  [vmeste-so-vsemi.ru](http://www.vmeste-so-vsemi.ru/wiki/%D0%A3%D1%87%D0%B0%D1%81%D1%82%D0%BD%D0%B8%D0%BA:MargaritaMahomet) then [utilize llm](https://www.buysellammo.com) -m [deepseek-reasoner 'timely'](https://www.fitmatures.com) to run [triggers](http://tabula-viae.de).<br>
 <br>This won't show you the [reasoning](https://mueblesalejandro.com) tokens, sadly. Those are served up by the API (example here) however LLM doesn't yet have a method to show them.<br>