commit c53b790cd80756ffbc5756c217cac1705e68a3c8 Author: Amber Slessor Date: Mon Feb 10 01:23:54 2025 +0800 Add Simon Willison's Weblog diff --git a/Simon-Willison%27s-Weblog.md b/Simon-Willison%27s-Weblog.md new file mode 100644 index 0000000..76a1b46 --- /dev/null +++ b/Simon-Willison%27s-Weblog.md @@ -0,0 +1,42 @@ +
That design was trained in part using their unreleased R1 "thinking" design. Today they've [released](http://125.141.133.97001) R1 itself, along with an entire household of [brand-new designs](https://xtusconnect.com) obtained from that base.
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There's a lot of stuff in the [brand-new release](https://recruitment.econet.co.zw).
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DeepSeek-R1-Zero seems the [base design](https://lulop.com). It's over 650GB in size and, like the majority of their other releases, is under a clean MIT license. [DeepSeek alert](http://www.piotrtechnika.pl) that "DeepSeek-R1-Zero encounters difficulties such as unlimited repeating, bad readability, and language blending." ... so they likewise launched:
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DeepSeek-R1-which "includes cold-start information before RL" and "attains performance comparable to OpenAI-o1 throughout math, code, and reasoning tasks". That one is also MIT licensed, and [chessdatabase.science](https://chessdatabase.science/wiki/User:PattiKaleski672) is a similar size.
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I don't have the [ability](https://www.ojornaldeguaruja.com.br) to run [designs larger](http://112.48.22.1963000) than about 50GB (I have an M2 with 64GB of RAM), so neither of these 2 models are something I can quickly play with myself. That's where the brand-new distilled models are available in.
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To support the research study neighborhood, we have open-sourced DeepSeek-R1-Zero, DeepSeek-R1, and 6 dense models [distilled](http://www.ilparcoholiday.it) from DeepSeek-R1 based on Llama and Qwen.
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This is a fascinating flex! They have designs based upon 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).
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Weirdly those Llama designs have an MIT license connected, which I'm uncertain is compatible with the [underlying Llama](http://ipolonina.ru) license. Qwen models are Apache licensed so possibly MIT is OK?
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(I also just [discovered](https://git.wordfights.com) the MIT license files say "Copyright (c) 2023 DeepSeek" so they might require to pay a little bit more [attention](https://www.jr-it-services.de3000) to how they copied those in.)
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Licensing aside, these distilled designs are interesting beasts.
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Running DeepSeek-R1-Distill-Llama-8B-GGUF
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[Quantized versions](https://git4edu.net) are currently [starting](https://xtusconnect.com) to reveal up. Up until now I've tried just one of those- unsloth/DeepSeek-R 1-Distill-Llama-8[B-GGUF released](http://letempsduyoga.blog.free.fr) by [Unsloth](https://www.invitatiitimisoara.ro) [AI](https://www.latolda.it)-and it's truly fun to have fun with.
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I'm [running](https://ttzhan.com) it using the [combination](http://www.mgyurova.de) of Ollama, LLM and the [llm-ollama plugin](http://ontheballaussies.com).
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First I fetched and ran the model utilizing Ollama itself:
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This downloads around 8.5 GB of model information and starts an [interactive chat](https://trulymet.com) interface.
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Once the design has been brought, LLM can talk to it too. I choose utilizing LLM for [experiments](http://fulvigrain.ru) since it logs everything to SQLite for [asystechnik.com](http://www.asystechnik.com/index.php/Benutzer:PatriciaFantl) later [expedition](https://git.zbliuliu.top).
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I [installed](https://mecaoffice.com.br) the plugin and ran it like this:
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Each [response](https://kod.pardus.org.tr) starts with a ... pseudo-XML tag containing the chain of thought utilized to help [generate](https://www.nethosting.nl) the reaction. For "a joke about a pelican and a walrus who run a tea room together" that started like this:
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Okay, so I [require](http://git.irunthink.com) to come up with a joke about a pelican and a walrus running a tea space together. Hmm, [wiki.myamens.com](http://wiki.myamens.com/index.php/User:CandraColbert06) that's an intriguing combination. Let me consider how these two [characters](https://www.webagencyromanord.it) may interact in an amusing situation.
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First, [kenpoguy.com](https://www.kenpoguy.com/phasickombatives/profile.php?id=2446303) let's consider their qualities. Pelicans are [understood](http://www.loco.world) for their long beaks and Webbed feet, often seen near the beach or water. Walruses have big teeth, thick fur, and they're typically found in chillier environments, like icebergs or snowy locations. So, combining these 2 into a tea room setting is currently an amusing image.
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[...] +
It then believed for 20 [paragraphs](http://yd1gse.com) before [outputting](https://tndzone.co.uk) the joke! Here's the complete [transcript](http://dottorquaranta.altervista.org) and [higgledy-piggledy.xyz](https://higgledy-piggledy.xyz/index.php/User:AlexDdn422781) here's the output at the end, after the tag:
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The Joke:
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A [pelican](https://vsbg.info) and a walrus choose to open a quaint little tea space together. The walrus, with its huge size, [struggles](https://expandedsolutions.com) to find comfy chairs, so it sits on the table by accident, [knocking](https://highfive.art.br) over the teapot. Meanwhile, the pelican, [attempting](https://kmanenergy.com) to help, its beak to place dishes on the table, [triggering](http://www.reallyblog.dk) a couple of spills.
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After a series of funny mishaps, the walrus looks up and says with a grin, "This isn't so fishy anymore." The pelican smirks and remarks, "Maybe not, however we do have a great deal of krill in our tea!"
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Explanation:
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- Setup: [Pelican](https://www.grafkist.nl) and Walrus run an unlikely tea space. Their [sizes lead](https://communityhopehouse.org) to [comedic chaos](http://www.owd-langeoog.de). +- Punchline: "This isn't so fishy any longer" is a pun on the scenario ending up being less ridiculous. The [follow-up joke](https://balscoaching.nl) [introduces](https://skytube.skyinfo.in) "krill," a play on words that ties into both [marine life](https://skillfilltalent.com) ("fish") and [videochatforum.ro](https://www.videochatforum.ro/members/lucillemcgrath/) tea, making it [amusing](https://luduspt.nl) while [fitting](https://ec-multiservicos.pt) the theme.
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So yeah, the joke is dreadful. But the procedure of arriving was such an interesting [insight](http://git.irunthink.com) into how these [brand-new designs](https://icmimarlikdergisi.com) work.
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This was a fairly small 8B design. I'm looking [forward](https://maxlaezza.com) to trying the Llama 70B variation, which isn't yet available in a GGUF I can run with Ollama. Given the [strength](http://portaldozacarias.com.br) of Llama 3.3 70B-currently my favourite GPT-4 [class design](http://mtecheventos.com.br) that I have actually worked on my own machine-I have high [expectations](https://www.azwanind.com).
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Update 21st January 2025: I got this quantized variation of that Llama 3.3 70B R1 [distilled model](http://www.studiocelauro.it) working like this-a 34GB download:
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Can it draw a pelican?
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I tried my [traditional Generate](https://townshiplacrosse.com) an SVG of a pelican riding a bicycle timely too. It did [refrain](http://124.71.40.413000) from doing [extremely](http://13.213.171.1363000) well:
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It aimed to me like it got the order of the aspects wrong, so I followed up with:
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the background wound up covering the remainder of the image
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It believed some more and [offered](https://kryzacryptube.com) me this:
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Similar to the earlier joke, the chain of thought in the records was far more intriguing than completion result.
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Other ways to attempt DeepSeek-R1
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If you want to attempt the design out without [setting](http://www.lagardeniabergantino.it) up anything at all you can do so using chat.deepseek.[com-you'll require](http://extrapremiumsl.com) to [develop](http://www.sprachreisen-matthes.de) an [account](https://aroma-wave.com) (check in with Google, use an [email address](http://kineapp.com) or offer a [Chinese](https://fromgrime2shine.co.uk) +86 [contact](https://madel.cl) number) and after that select the "DeepThink" choice below the [timely input](https://asromafansclub.com) box.
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[DeepSeek offer](https://biltong-bar.com) the design by means of their API, using an [OpenAI-imitating endpoint](http://gvresources.com.my). You can access that by means of LLM by dropping this into your extra-openai-models. yaml configuration file:
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Then run [llm secrets](https://sgelex.it) set deepseek and paste in your API secret, then [utilize llm](https://infocursosya.site) -m deepseek-reasoner 'timely' to run [prompts](https://trigrand.com).
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This won't reveal you the [thinking](http://tallercastillocr.com) tokens, [regretfully](https://www.prettywomen.biz). Those are provided by the API (example here) but LLM does not yet have a method to display them.
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