Found 36 results for "tag:llm"

• 14 Charts That Tell the Story of AI Right Now

  https://www.newcomer.co/p/14-charts-that-tell-the-story-of?utm_source=www.technofobia.pl&utm_medium=newsletter&utm_campaign=linkowisko-89-technofobia

  Data on Elo rankings, memory tokens, GitHub repos, domain registrations & more

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• A comprehensive guide to running Llama 2 locally

  https://replicate.com/blog/run-llama-locally

  How to run Llama 2 on Mac, Linux, Windows, and your phone.

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• AgentGPT: Autonomous AI Agents in your Browser - KDnuggets

  https://www.kdnuggets.com/2023/06/agentgpt-autonomous-ai-agents-browser.html

  Give your AI agent a name and goal, and watch it accomplish the assigned objective.

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• Ask HN: What have you built with LLMs? | Hacker News

  https://news.ycombinator.com/item?id=39263664&utm_source=hackernewsletter&utm_medium=email&utm_term=ask_hn

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• Bash One-Liners for LLMs

  https://justine.lol/oneliners/?utm_source=hackernewsletter&utm_medium=email&utm_term=code

  Tutorial on how llamafile makes LLMs shell scriptable.

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• Building LLM applications for production

  https://huyenchip.com/2023/04/11/llm-engineering.html?utm_source=substack&utm_medium=email#can_llms_do_data_analysis_for_me

  It's easy to make something cool with LLMs, but very hard to make something production-ready with them. Large language models' (LLMs) limitations are exacerbated by a lack of engineering rigor in prompt engineering, partially due to the ambiguous nature of natural languages, and partially due to the nascent nature of the field. This post discusses how LLMs will change MLOps workflows.

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• Building LLMs from the Ground Up: A 3-hour Coding Workshop

  https://www.youtube.com/watch?v=quh7z1q7-uc

  REFERENCES:1. Build an LLM from Scratch book: https://mng.bz/M96o2. Build an LLM from Scratch repo: https://github.com/rasbt/LLMs-from-scratch3. GitHub repos...

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• Building Real-World Applications With Large Language Models | Udacity

  https://www.udacity.com/course/building-real-world-applications-with-large-language-models--cd13455?utm_campaign=acq_100_2024-02-21_ndxxx_new-courses-roundup-february_global&utm_source=blueshift&utm_medium=email&utm_content=acq_100_2024-02-21_ndxxx_new-courses-roundup-february_global&bsft_txnid=02a8afda-55ea-44bd-b30f-d894c6a8a5b5&bsft_mime_type=html&bsft_lx=14&bsft_tv=38

  Unlock the power of Large Language Models (LLMs) with Udacity's free LLMOps course. Learn to build real-world applications with LLMs using the latest tools and techniques in the field.

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• Dynamic documents // LLMs + end-user programming

  https://www.geoffreylitt.com/2022/11/23/dynamic-documents

  Dynamic documents as personal software, and reflections on the role of AI in end-user programming...

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• Eight Things to Know about Large Language Models

  https://arxiv.org/abs/2304.00612?utm_source=substack&utm_medium=email

  The widespread public deployment of large language models (LLMs) in recent months has prompted a wave of new attention and engagement from advocates, policymakers, and scholars from many fields. This attention is a timely response to the many urgent questions that this technology raises, but it can sometimes miss important considerations. This paper surveys the evidence for eight potentially surprising such points: 1. LLMs predictably get more capable with increasing investment, even without targeted innovation. 2. Many important LLM behaviors emerge unpredictably as a byproduct of increasing investment. 3. LLMs often appear to learn and use representations of the outside world. 4. There are no reliable techniques for steering the behavior of LLMs. 5. Experts are not yet able to interpret the inner workings of LLMs. 6. Human performance on a task isn't an upper bound on LLM performance. 7. LLMs need not express the values of their creators nor the values encoded in web text. 8. Brief interactions with LLMs are often misleading.

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• Falcon - A guide to finetune and inference - Lightning AI

  https://lightning.ai/pages/blog/falcon-a-guide-to-finetune-and-inference/?ml_recipient=91126110137353962&ml_link=91126107875575214

  Falcon is the latest open-source large language model released by Technology Innovation Institute. It is an autoregressive decoder-only model with two variants: a 7 billion parameter model and a 40 billion parameter model. The 40B model variant was trained on 384 GPUs on AWS for 2 months. We have integrated Falcon into Lit-Parrot. You... Read more »

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• Generative AI exists because of the transformer

  https://ig.ft.com/generative-ai/?utm_source=unknownews

  The technology has resulted in a host of cutting-edge AI applications — but its real power lies beyond text generation

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• GitHub - vanna-ai/vanna: 🤖 Chat with your SQL database 📊. Accurate Text-to-SQL Generation via LLMs using RAG 🔄.

  https://github.com/vanna-ai/vanna

  🤖 Chat with your SQL database 📊. Accurate Text-to-SQL Generation via LLMs using RAG 🔄. - GitHub - vanna-ai/vanna: 🤖 Chat with your SQL database 📊. Accurate Text-to-SQL Generation via LLMs using RAG 🔄.

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• Google Cloud Skills Boost

  https://www.cloudskillsboost.google/journeys/118?utm_source=unknownews

  Qwiklabs provides real Google Cloud environments that help developers and IT professionals learn cloud platforms and software, such as Firebase, Kubernetes and more.

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• Home | Marginlab

  https://marginlab.ai/

  Rigorous LLM benchmarks you can trust. Industry-specific evaluations with transparent methodology.

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• How LLMs Actually Work

  https://www.0xkato.xyz/how-llms-actually-work/

  A from-the-ground-up walkthrough of how modern LLMs work, from tokens to transformer blocks to the next-token loop

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• How LLMs Work — A Visual Deep Dive

  https://ynarwal.github.io/how-llms-work/

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• LLM API Pricing Data - Price Per Token

  https://pricepertoken.com/?utm_source=hackernewsletter&utm_medium=email&utm_term=show_hn

  Compare pricing for LLM APIs including OpenAI GPT-4, Anthropic Claude, Google Gemini and more. Updated daily with official pricing.

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• LLM Powered Autonomous Agents

  https://lilianweng.github.io/posts/2023-06-23-agent/?ml_recipient=92389183911363954&ml_link=92389182271391600&utm_source=newsletter&utm_medium=email&utm_term=2023-07-03&utm_campaign=+Data+Science+News+16+SoundStorm+Midjourney+v+5+2+50+robot+w+na+szczycie+ONZ+Kurs+Data+Science+od+IBM+MotionGPT

  Building agents with LLM (large language model) as its core controller is a cool concept. Several proof-of-concepts demos, such as AutoGPT, GPT-Engineer and BabyAGI, serve as inspiring examples. The potentiality of LLM extends beyond generating well-written copies, stories, essays and programs; it can be framed as a powerful general problem solver. Agent System Overview In a LLM-powered autonomous agent system, LLM functions as the agent’s brain, complemented by several key components:

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• LangChain: Chat with Your Data

  https://www.deeplearning.ai/short-courses/langchain-chat-with-your-data/?utm_campaign=langchain-launch&utm_medium=email&_hsmi=265152429&_hsenc=p2ANqtz-8LeA-etpkAH0wpd-MEP19jjwkXYiQgV5YivNV4K3e4RJzPcqGbr3c4xcEliJ4-sbhwIM_nyRtrd-fMeJP36LLC3iZf6DFDD0IhDjYsBSdvc0DVCvM&utm_content=265152429&utm_source=hs_email

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• Lekcje na temat LLM-ów

  https://lekcje.aidevs.pl/

  Co kilka dni wyślemy Ci na maila lekcje, które poszerzą Twoją wiedzę na temat modeli językowych i baz wektorowych.

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• Mozilla-Ocho/llamafile: Distribute and run LLMs with a single file.

  https://github.com/Mozilla-Ocho/llamafile

  Distribute and run LLMs with a single file. Contribute to Mozilla-Ocho/llamafile development by creating an account on GitHub.

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• OpenRouter Python SDK | Complete Documentation | OpenRouter | Documentation

  https://openrouter.ai/docs/sdks/python?utm_campaign=updates-19nov2025&utm_content=update-19nov2025&utm_medium=email_action&utm_source=customer.io

  Complete guide to using the OpenRouter Python SDK. Learn how to integrate AI models into your Python applications.

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• Portkey-AI/gateway: A Blazing Fast AI Gateway. Route to 100+ LLMs with 1 fast & friendly API.

  https://github.com/Portkey-AI/gateway?utm_source=unknownews

  A Blazing Fast AI Gateway. Route to 100+ LLMs with 1 fast & friendly API. - Portkey-AI/gateway: A Blazing Fast AI Gateway. Route to 100+ LLMs with 1 fast & friendly API.

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• Python & JavaScript Libraries · Ollama Blog

  https://ollama.ai/blog/python-javascript-libraries?utm_source=hackernewsletter&utm_medium=email&utm_term=code

  The initial versions of the Ollama Python and JavaScript libraries are now available, making it easy to integrate your Python or JavaScript, or Typescript app with Ollama in a few lines of code. Both libraries include all the features of the Ollama REST API, are familiar in design, and compatible with new and previous versions of Ollama.

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• Reor

  https://www.reorproject.org/?utm_source=unknownews

  AI note-taking app that runs models locally & offline on your computer.

  llm

• TRON Format

  https://tron-format.github.io/?utm_source=weekbyte&utm_medium=email&utm_term=2025-12-16&utm_campaign=Why+I+stopped+using+JSON+in+APIs+and+switched+to+Protobuf+do+you+really+need+microservices+and+why+can+t+you+focus+at+work+

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• The Full Stack - LLM Bootcamp

  https://fullstackdeeplearning.com/llm-bootcamp/

  Best practices and tools for building LLM-powered apps

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• Top Free Courses on Large Language Models - KDnuggets

  https://www.kdnuggets.com/2023/03/top-free-courses-large-language-models.html

  Interested in learning how ChatGPT and other AI chatbots work under the hood? Look no further. Check out these free courses and resources on large language models from Stanford, Princeton, ETH, and more.

  llm

• Turn websites into knowledge bases

  https://www.embedding.io/#pricing

  Turn any website into a knowledge base for LLMs with Embedding.io. Easily crawl, chunk, and vectorize web content for seamless integration with large language models. Start for free and explore our powerful API for efficient data collection and querying.

  llm

• cheahjs/free-llm-api-resources: A list of free LLM inference resources accessible via API.

  https://github.com/cheahjs/free-llm-api-resources

  A list of free LLM inference resources accessible via API. - cheahjs/free-llm-api-resources

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• https://dataworkshop.eu/llm-demo?utm_source=YouTube&utm_campaign=demo-llm&utm_term=JbDmQbYRfTw&utm_content=dataworkshop

  https://dataworkshop.eu/llm-demo?utm_source=YouTube&utm_campaign=demo-llm&utm_term=JbDmQbYRfTw&utm_content=dataworkshop

  llm

• nilsherzig/LLocalSearch: LLocalSearch is a completely locally running search aggregator using LLM Agents. The user can ask a question and the system will use a chain of LLMs to find the answer. The user can see the progress of the agents and the final answer. No OpenAI or Google API keys are needed.

  https://github.com/nilsherzig/LLocalSearch?utm_source=hackernewsletter&utm_medium=email&utm_term=show_hn

  LLocalSearch is a completely locally running search aggregator using LLM Agents. The user can ask a question and the system will use a chain of LLMs to find the answer. The user can see the progres...

  llm

• rasbt/LLMs-from-scratch: Implementing a ChatGPT-like LLM from scratch, step by step

  https://github.com/rasbt/LLMs-from-scratch?utm_source=hackernewsletter&utm_medium=email&utm_term=books

  Implementing a ChatGPT-like LLM from scratch, step by step - rasbt/LLMs-from-scratch: Implementing a ChatGPT-like LLM from scratch, step by step

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• rashadphz/farfalle: 🔍 AI search engine - self-host with local or cloud LLMs

  https://github.com/rashadphz/farfalle?tab=readme-ov-file

  🔍 AI search engine - self-host with local or cloud LLMs - rashadphz/farfalle

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• 👾 LM Studio - Discover and run local LLMs

  https://lmstudio.ai/?utm_source=unknownews

  Find, download, and experiment with local LLMs

  llm