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#finetuning

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LLMsFine-tuning LLMs for Tool Use How to get models to search the web, run code, and do your taxes Continue reading on Medium » <br><br><a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/data-science" target="_blank">#data-science</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/ai" target="_blank">#ai</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/llm" target="_blank">#llm</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/fine-tuning" target="_blank">#fine-tuning</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/machine-learning" target="_blank">#machine-learning</a><br><br><a href="https://shawhin.medium.com/fine-tuning-llms-for-tool-use-5f1db03d7c55?source=rss------machine_learning-5" rel="nofollow noopener" target="_blank">Origin</a> | <a href="https://awakari.com/sub-details.html?id=LLMs" rel="nofollow noopener" target="_blank">Interest</a> | <a href="https://awakari.com/pub-msg.html?id=ZPqNSOL5IuLSEB8Xs7qMymgKJ2u&amp;interestId=LLMs" rel="nofollow noopener" target="_blank">Match</a>
LLMsFine-Tuning Isn’t Always Fine “In our quest to teach machines more, we often forget how much they already know.” Continue reading on Medium » <br><br><a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/fine-tuning" target="_blank">#fine-tuning</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/rags" target="_blank">#rags</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/machine-learning" target="_blank">#machine-learning</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/llm" target="_blank">#llm</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/ai-engineering" target="_blank">#ai-engineering</a><br><br><a href="https://medium.com/@smquasim016/fine-tuning-isnt-always-fine-1ece2013cf62?source=rss------machine_learning-5" rel="nofollow noopener" target="_blank">Origin</a> | <a href="https://awakari.com/sub-details.html?id=LLMs" rel="nofollow noopener" target="_blank">Interest</a> | <a href="https://awakari.com/pub-msg.html?id=RdxgILB4ZjX36x8cqoMhvvPilhA&amp;interestId=LLMs" rel="nofollow noopener" target="_blank">Match</a>
LLMsFine-Tuning, Prompt Fine-Tuning, and Prompt Engineering Discover the Key Differences and When to Use Each for Superior Results Continue reading on Level Up Coding » <br><br><a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/llm" target="_blank">#llm</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/fine-tuning" target="_blank">#fine-tuning</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/machine-learning" target="_blank">#machine-learning</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/artificial-intelligence" target="_blank">#artificial-intelligence</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/generative-ai-tools" target="_blank">#generative-ai-tools</a><br><br><a href="https://levelup.gitconnected.com/fine-tuning-prompt-fine-tuning-and-prompt-engineering-c8ccfe51deeb?source=rss------machine_learning-5" rel="nofollow noopener" target="_blank">Origin</a> | <a href="https://awakari.com/sub-details.html?id=LLMs" rel="nofollow noopener" target="_blank">Interest</a> | <a href="https://awakari.com/pub-msg.html?id=5kZ3QG8lo61s5V5As0Cxtu3W2ts&amp;interestId=LLMs" rel="nofollow noopener" target="_blank">Match</a>
Alvin Ashcraft 🐿️<p>AI Toolkit for VS Code July Update | by Junjie Li.</p><p><a href="https://techcommunity.microsoft.com/blog/azuredevcommunityblog/ai-toolkit-for-vs-code-july-update/4431548" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">techcommunity.microsoft.com/bl</span><span class="invisible">og/azuredevcommunityblog/ai-toolkit-for-vs-code-july-update/4431548</span></a></p><p><a href="https://hachyderm.io/tags/aitoolkit" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>aitoolkit</span></a> <a href="https://hachyderm.io/tags/vscode" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vscode</span></a> <a href="https://hachyderm.io/tags/ai" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ai</span></a> <a href="https://hachyderm.io/tags/github" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>github</span></a> <a href="https://hachyderm.io/tags/aimodels" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>aimodels</span></a> <a href="https://hachyderm.io/tags/finetuning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>finetuning</span></a></p>
LLMsFine-Tuning vs. RAG: How to Decide for Your LLM Project Large Language Models (LLMs) have transformed the way we build applications — from chatbots to document summarization to question… Co...<br><br><a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/fine-tuning" target="_blank">#fine-tuning</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/llm" target="_blank">#llm</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/generative-ai-use-cases" target="_blank">#generative-ai-use-cases</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/retrieval-augmented-gen" target="_blank">#retrieval-augmented-gen</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/machine-learning" target="_blank">#machine-learning</a><br><br><a href="https://medium.com/@saravananpalanisamy_54774/fine-tuning-vs-rag-how-to-decide-for-your-llm-project-15201cf5c2ac?source=rss------machine_learning-5" rel="nofollow noopener" target="_blank">Origin</a> | <a href="https://awakari.com/sub-details.html?id=LLMs" rel="nofollow noopener" target="_blank">Interest</a> | <a href="https://awakari.com/pub-msg.html?id=MQx3uk4MGlZ8jYKRemDLaCaOU8O&amp;interestId=LLMs" rel="nofollow noopener" target="_blank">Match</a>
LLMsText-to-LoRA: мгновенная адаптация трансформеров 😎 Следуй за белым кроликом 💊 📌 Telegram&nbsp;@TheWeeklyBrief&nbsp;— краткие обзо...<br><br><a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/AI" target="_blank">#AI</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/finetuning" target="_blank">#finetuning</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/Hypernetwork" target="_blank">#Hypernetwork</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/llm" target="_blank">#llm</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/lora" target="_blank">#lora</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/ml" target="_blank">#ml</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/sakana" target="_blank">#sakana</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/TextToLoRA" target="_blank">#TextToLoRA</a><br><br><a href="https://www.pvsm.ru/ai/424457" rel="nofollow noopener" target="_blank">Origin</a> | <a href="https://awakari.com/sub-details.html?id=LLMs" rel="nofollow noopener" target="_blank">Interest</a> | <a href="https://awakari.com/pub-msg.html?id=EGhYTR95NpgnEwRADN91y9NS8jA&amp;interestId=LLMs" rel="nofollow noopener" target="_blank">Match</a>
LLMsText-to-LoRA: мгновенная адаптация трансформеров Исследователи Sakana AI разработали&nbsp; Text-to-LoRA (T2L) , гиперсеть, котора...<br><br><a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/ai" target="_blank">#ai</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/ml" target="_blank">#ml</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/llm" target="_blank">#llm</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/lora" target="_blank">#lora</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/sakana" target="_blank">#sakana</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/TextToLoRA" target="_blank">#TextToLoRA</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/Hypernetwork" target="_blank">#Hypernetwork</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/finetuning" target="_blank">#finetuning</a><br><br><a href="https://habr.com/ru/articles/925404/?utm_source=habrahabr&amp;utm_medium=rss&amp;utm_campaign=925404" rel="nofollow noopener" target="_blank">Origin</a> | <a href="https://awakari.com/sub-details.html?id=LLMs" rel="nofollow noopener" target="_blank">Interest</a> | <a href="https://awakari.com/pub-msg.html?id=HUrGJlWIOz6AnzA1thdikCRyXmC&amp;interestId=LLMs" rel="nofollow noopener" target="_blank">Match</a>
Habr<p>Text-to-LoRA: мгновенная адаптация трансформеров</p><p>Исследователи Sakana AI разработали Text-to-LoRA (T2L) , гиперсеть, которая динамически генерирует веса Low-Rank Adaptation (LoRA) для больших языковых моделей на основе описаний целевых задач на естественном языке. Этот метод обеспечивает эффективную адаптацию без предварительной настройки (zero-shot), превосходя установленные базовые показатели и достигая производительности, сравнимой с тонко настроенными адаптерами на ранее не встречавшихся задачах.</p><p><a href="https://habr.com/ru/articles/925404/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">habr.com/ru/articles/925404/</span><span class="invisible"></span></a></p><p><a href="https://zhub.link/tags/ai" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ai</span></a> <a href="https://zhub.link/tags/ml" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ml</span></a> <a href="https://zhub.link/tags/llm" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>llm</span></a> <a href="https://zhub.link/tags/lora" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>lora</span></a> <a href="https://zhub.link/tags/sakana" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>sakana</span></a> <a href="https://zhub.link/tags/TextToLoRA" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TextToLoRA</span></a> <a href="https://zhub.link/tags/Hypernetwork" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Hypernetwork</span></a> <a href="https://zhub.link/tags/finetuning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>finetuning</span></a></p>
LLMsProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models The key idea The key idea Reinforcement learning (RL) has had a resurgence in LLMs with application to ...<br><br><a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/LLMs" target="_blank">#LLMs</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/training-dynamics" target="_blank">#training-dynamics</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/fine-tuning" target="_blank">#fine-tuning</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/reasoning" target="_blank">#reasoning</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/reinforcement-learning" target="_blank">#reinforcement-learning</a><br><br><a href="https://graphcore-research.github.io/prorl/" rel="nofollow noopener" target="_blank">Origin</a> | <a href="https://awakari.com/sub-details.html?id=LLMs" rel="nofollow noopener" target="_blank">Interest</a> | <a href="https://awakari.com/pub-msg.html?id=9N5KR0r2wXZVbgWCE3Sv9k3kf6e&amp;interestId=LLMs" rel="nofollow noopener" target="_blank">Match</a>
Irène Langlet<p>En train de commencer à utiliser <a href="https://piaille.fr/tags/calibre" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>calibre</span></a>, et très contente de l'éditeur de métadonnées par lot. Cette fonction "tester le résultat" existe-t-elle sur <a href="https://piaille.fr/tags/Zotero" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Zotero</span></a>? Ce serait drôlement pratique, et jusqu'ici je n'en ai pas vu.</p><p>(Certes je reviens d'un colloque où on me parlait de <a href="https://piaille.fr/tags/finetuning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>finetuning</span></a>, mais je ne suis pas en mesure d'utiliser ça pour nettoyer mes listes. Par contre on m'avait conseillé calibre depuis un bail.)</p>
Habr<p>[Перевод] Кто, как и зачем внедряет Gen AI в 2025: опыт 100 CIO</p><p>Чуть больше года назад мы выделили 16 ключевых изменений в том, как компании подходили к разработке и закупке генеративных ИИ. С тех пор ландшафт продолжил стремительно эволюционировать, поэтому мы снова провели беседы с более чем двумя десятками корпоративных заказчиков и опросили 100 CIO из 15 отраслей, чтобы помочь фаундерам понять, как в 2025 в корпорациях используют, приобретают и закладывают бюджеты под generative AI . Даже в такой динамичной сфере, где единственная постоянная — это перемены, структура рынка genAI изменилась куда сильнее, чем мы ожидали после прошлого исследования.</p><p><a href="https://habr.com/ru/articles/923112/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">habr.com/ru/articles/923112/</span><span class="invisible"></span></a></p><p><a href="https://zhub.link/tags/genai" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>genai</span></a> <a href="https://zhub.link/tags/ai" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ai</span></a> <a href="https://zhub.link/tags/%D0%B8%D0%B8" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ии</span></a> <a href="https://zhub.link/tags/%D0%B3%D0%B5%D0%BD%D0%B5%D1%80%D0%B0%D1%82%D0%B8%D0%B2%D0%BD%D1%8B%D0%B9_%D0%B8%D0%B8" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>генеративный_ии</span></a> <a href="https://zhub.link/tags/llm" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>llm</span></a> <a href="https://zhub.link/tags/finetuning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>finetuning</span></a> <a href="https://zhub.link/tags/openai" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>openai</span></a> <a href="https://zhub.link/tags/anthropic" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>anthropic</span></a></p>
LLMs[Перевод] Кто, как и зачем внедряет Gen AI в 2025: опыт 100 CIO Чуть больше года назад мы выделили 16 ключевых изменени...<br><br><a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/genai" target="_blank">#genai</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/ai" target="_blank">#ai</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/ии" target="_blank">#ии</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/генеративный" target="_blank">#генеративный</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/ии" target="_blank">#ии</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/llm" target="_blank">#llm</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/fine-tuning" target="_blank">#fine-tuning</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/openai" target="_blank">#openai</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/anthropic" target="_blank">#anthropic</a><br><br><a href="https://habr.com/ru/articles/923112/?utm_source=habrahabr&amp;utm_medium=rss&amp;utm_campaign=923112" rel="nofollow noopener" target="_blank">Origin</a> | <a href="https://awakari.com/sub-details.html?id=LLMs" rel="nofollow noopener" target="_blank">Interest</a> | <a href="https://awakari.com/pub-msg.html?id=Pp9KLCWHR7rsk8Gv5qIKIcjAl8K&amp;interestId=LLMs" rel="nofollow noopener" target="_blank">Match</a>
LLMs<br><br><a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/AI" target="_blank">#AI</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/AI" target="_blank">#AI</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/research" target="_blank">#research</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/AI," target="_blank">#AI,</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/ML" target="_blank">#ML</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/and" target="_blank">#and</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/Deep" target="_blank">#Deep</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/Learning" target="_blank">#Learning</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/Fine-tuning" target="_blank">#Fine-tuning</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/large" target="_blank">#large</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/language" target="_blank">#language</a><br><br><a href="https://venturebeat.com/ai/beyond-static-ai-mits-new-framework-lets-models-teach-themselves/" rel="nofollow noopener" target="_blank">Origin</a> | <a href="https://awakari.com/sub-details.html?id=LLMs" rel="nofollow noopener" target="_blank">Interest</a> | <a href="https://awakari.com/pub-msg.html?id=3laUm5TIM1tpnnKbKnkJ913Ukl6&amp;interestId=LLMs" rel="nofollow noopener" target="_blank">Match</a>
LLMsTrain Big, Tune Tiny: A Practical Guide to LoRA-Based Fine-Tuning of LLMs Explore how LoRA provides a lightweight alternative to full fine-tuning, compared to prompt engineering and other LLM adapt...<br><br><a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/large-language-models" target="_blank">#large-language-models</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/fine-tuning" target="_blank">#fine-tuning</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/nlp" target="_blank">#nlp</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/artificial-intelligence" target="_blank">#artificial-intelligence</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/machine-learning" target="_blank">#machine-learning</a><br><br><a href="https://medium.com/@aman.khokhar01/train-big-tune-tiny-a-practical-guide-to-lora-based-fine-tuning-of-llms-654d5c2a4409?source=rss------machine_learning-5" rel="nofollow noopener" target="_blank">Origin</a> | <a href="https://awakari.com/sub-details.html?id=LLMs" rel="nofollow noopener" target="_blank">Interest</a> | <a href="https://awakari.com/pub-msg.html?id=46SHDQZSw9wTC9mLy2Kmltsu6l6&amp;interestId=LLMs" rel="nofollow noopener" target="_blank">Match</a>
LLMsРазработка LLM моделей для обновления кода приложений на более высокие версии фреймворков или языков програ...<br><br><a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/llm" target="_blank">#llm</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/rl" target="_blank">#rl</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/express.js" target="_blank">#express.js</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/nest.js" target="_blank">#nest.js</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/python" target="_blank">#python</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/gpt" target="_blank">#gpt</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/rag" target="_blank">#rag</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/llama" target="_blank">#llama</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/fine-tuning" target="_blank">#fine-tuning</a><br><br><a href="https://habr.com/ru/articles/920424/?utm_source=habrahabr&amp;utm_medium=rss&amp;utm_campaign=920424" rel="nofollow noopener" target="_blank">Origin</a> | <a href="https://awakari.com/sub-details.html?id=LLMs" rel="nofollow noopener" target="_blank">Interest</a> | <a href="https://awakari.com/pub-msg.html?id=DrHQm0dyFLQKosLUpqZ4Sh2IIdM&amp;interestId=LLMs" rel="nofollow noopener" target="_blank">Match</a>
Habr<p>Разработка LLM моделей для обновления кода приложений на более высокие версии фреймворков или языков программирования</p><p>В этой статье я планирую исследовать, как можно использовать большие языковые модели (LLM) для миграции проектов между различными фреймворками. Применение LLM в задачах на уровне репозитория — это развивающаяся и всё более популярная область. Миграция кода со старых, устаревших фреймворков на новые является одной из ключевых задач в крупных корпоративных проектах.</p><p><a href="https://habr.com/ru/articles/920424/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">habr.com/ru/articles/920424/</span><span class="invisible"></span></a></p><p><a href="https://zhub.link/tags/llm" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>llm</span></a> <a href="https://zhub.link/tags/rl" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rl</span></a> <a href="https://zhub.link/tags/expressjs" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>expressjs</span></a> <a href="https://zhub.link/tags/nestjs" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>nestjs</span></a> <a href="https://zhub.link/tags/python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>python</span></a> <a href="https://zhub.link/tags/gpt" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>gpt</span></a> <a href="https://zhub.link/tags/rag" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rag</span></a> <a href="https://zhub.link/tags/llama" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>llama</span></a> <a href="https://zhub.link/tags/finetuning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>finetuning</span></a></p>
Alvin Ashcraft 🐿️<p>Getting Started with the AI Toolkit: A Beginner’s Guide with Demos and Resources.</p><p><a href="https://techcommunity.microsoft.com/blog/educatordeveloperblog/getting-started-with-the-ai-toolkit-a-beginner%E2%80%99s-guide-with-demos-and-resources/4425608" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">techcommunity.microsoft.com/bl</span><span class="invisible">og/educatordeveloperblog/getting-started-with-the-ai-toolkit-a-beginner%E2%80%99s-guide-with-demos-and-resources/4425608</span></a></p><p><a href="https://hachyderm.io/tags/vscode" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vscode</span></a> <a href="https://hachyderm.io/tags/ai" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ai</span></a> <a href="https://hachyderm.io/tags/aitoolkit" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>aitoolkit</span></a> <a href="https://hachyderm.io/tags/finetuning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>finetuning</span></a> <a href="https://hachyderm.io/tags/aimodels" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>aimodels</span></a> <a href="https://hachyderm.io/tags/modelcatalog" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>modelcatalog</span></a> <a href="https://hachyderm.io/tags/learning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>learning</span></a></p>
LLMsThe Next Word is Not Enough: How CAFT is Forcing a Rethink of LLM Fine-Tuning Concept-Aware Fine-Tuning, a method that democratizes multi-token prediction and could fundamentally change how we spec...<br><br><a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/ai" target="_blank">#ai</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/llm" target="_blank">#llm</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/fine-tuning" target="_blank">#fine-tuning</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/data-science" target="_blank">#data-science</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/machine-learning" target="_blank">#machine-learning</a><br><br><a href="https://medium.com/@jenray1986/the-next-word-is-not-enough-how-caft-is-forcing-a-rethink-of-llm-fine-tuning-e0ce7d969855?source=rss------machine_learning-5" rel="nofollow noopener" target="_blank">Origin</a> | <a href="https://awakari.com/sub-details.html?id=LLMs" rel="nofollow noopener" target="_blank">Interest</a> | <a href="https://awakari.com/pub-msg.html?id=Si3nGLRJSWuPEiUdzOnPdy5kXr6&amp;interestId=LLMs" rel="nofollow noopener" target="_blank">Match</a>
Hacker News<p>Fine-Tuning LLMs Is a Waste of Time</p><p><a href="https://codinginterviewsmadesimple.substack.com/p/fine-tuning-llms-is-a-huge-waste" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">codinginterviewsmadesimple.sub</span><span class="invisible">stack.com/p/fine-tuning-llms-is-a-huge-waste</span></a></p><p><a href="https://mastodon.social/tags/HackerNews" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>HackerNews</span></a> <a href="https://mastodon.social/tags/FineTuning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FineTuning</span></a> <a href="https://mastodon.social/tags/LLMs" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LLMs</span></a> <a href="https://mastodon.social/tags/WasteOfTime" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>WasteOfTime</span></a> <a href="https://mastodon.social/tags/AIResearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIResearch</span></a> <a href="https://mastodon.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> <a href="https://mastodon.social/tags/TechDebate" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TechDebate</span></a> <a href="https://mastodon.social/tags/Substack" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Substack</span></a></p>
LLMsWhat is Retrieval-Augmented Fine-Tuning (RAFT)? The world of Generative Pretrained Transformers (...<br><br><br><a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/AI" target="_blank">#AI</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/Generative" target="_blank">#Generative</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/AI" target="_blank">#AI</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/Large" target="_blank">#Large</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/Language" target="_blank">#Language</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/Models" target="_blank">#Models</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/fine" target="_blank">#fine</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/tuning" target="_blank">#tuning</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/Fine-tuning" target="_blank">#Fine-tuning</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/FT" target="_blank">#FT</a> <a rel="nofollow noopener" class="mention hashtag" href="https://mastodon.social/tags/IBM" target="_blank">#IBM</a><br><a href="https://www.franksworld.com/2025/06/09/what-is-retrieval-augmented-fine-tuning-raft/?utm_source=rss&amp;utm_medium=rss&amp;utm_campaign=what-is-retrieval-augmented-fine-tuning-raft" rel="nofollow noopener" target="_blank">Origin</a> | <a href="https://awakari.com/sub-details.html?id=LLMs" rel="nofollow noopener" target="_blank">Interest</a> | <a href="https://awakari.com/pub-msg.html?id=Jud3JmKWXjDnZUrazY5G8aD6Wgq&amp;interestId=LLMs" rel="nofollow noopener" target="_blank">Match</a>