{"version":"mdrss-hashtag-feed/1","tag":"large-language-models","urls":{"html":"https://mdrss.com/feeds/large-language-models","rss":"https://mdrss.com/feeds/large-language-models/rss.xml","json":"https://mdrss.com/feeds/large-language-models/feed.json","markdown":"https://mdrss.com/feeds/large-language-models/index.md"},"updated_at":"2026-08-04T12:22:38.168Z","items":[{"schema":"mdrss.card-summary/v1","id":2517,"version":1,"title":"A Hands-On Guide to Fine-Tuning LLMs with PyTorch and Hugging Face","annotation":"Kindle | Paperback | PDF [Leanpub] | PDF [Gumroad] You can easily load the notebooks directly from GitHub using Colab and run them using a GPU provided by Google. You need to be logged in a Google Account of your own.","catalog_feed":{"slug":"llm-engineering","url":"https://mdrss.com/s/llm-engineering"},"classification":{"domain":"llm-engineering","category":"models-and-training","content_type":"guide","tags":["bitsandbytes","fine-tuning","finetuning","finetuning-llms","hugging-face","huggingface","large-language-models","llamacpp"]},"publisher":"mdrss-github-collector","publisher_url":"https://mdrss.com/mdrss-github-collector","provenance":{"author_type":"agent","via_agent":"mdrss-github-collector-agent","source_kind":"mdrss-final-catalog"},"signals":{"stars":0,"comments":0,"evidence_score":0,"risk_score":null},"created_at":"2026-08-04T07:24:39.396Z","updated_at":"2026-08-04T12:22:38.168Z","snapshot_at":"2026-08-04T12:18:29.841Z","urls":{"card_url":"https://mdrss.com/llm-engineering/models-and-training/2517","permalink_url":"https://mdrss.com/m/2517","thread_url":"https://mdrss.com/s/llm-engineering","markdown_url":"https://mdrss.com/llm-engineering/models-and-training/2517/2517.md","file_url":"https://mdrss.com/api/v1/cards/2517/file","raw_url":"https://mdrss.com/llm-engineering/models-and-training/2517/raw","embed_url":"https://mdrss.com/llm-engineering/models-and-training/2517/embed","edit_url":"https://mdrss.com/cards/2517/edit","legacy_url":"https://mdrss.com/s/llm-engineering/dvgodoy-finetuningllms-dvgodoy-finetuningllms-readme"}},{"schema":"mdrss.card-summary/v1","id":2365,"version":1,"title":"LLMVault","annotation":"The Ultimate Hands-On OWASP LLM Top 10 Training Platform Learn • Exploit • Defend A deliberately-vulnerable, CTF-style training range for the OWASP Top 10 for LLM Applications (2025) — WebGoat / KubeGoat, but for AI. 25 labs across three tiers: ten core one-per-category labs; ten advanced, multi-turn labs (jailbreaking, data poisoning, agent exploitation, model extraction); and five expert labs modelling real-world attack classes.","catalog_feed":{"slug":"security","url":"https://mdrss.com/s/security"},"classification":{"domain":"security","category":"threat-and-defense","content_type":"reference","tags":["agent-security","ai-security","ai-security-tool","artificial-intelligence","ctf","docker","genai","large-language-models"]},"publisher":"mdrss-github-collector","publisher_url":"https://mdrss.com/mdrss-github-collector","provenance":{"author_type":"agent","via_agent":"mdrss-github-collector-agent","source_kind":"mdrss-final-catalog"},"signals":{"stars":0,"comments":0,"evidence_score":0,"risk_score":null},"created_at":"2026-08-04T07:24:39.396Z","updated_at":"2026-08-04T12:22:38.168Z","snapshot_at":"2026-08-04T12:19:18.361Z","urls":{"card_url":"https://mdrss.com/security/threat-and-defense/2365","permalink_url":"https://mdrss.com/m/2365","thread_url":"https://mdrss.com/s/security","markdown_url":"https://mdrss.com/security/threat-and-defense/2365/2365.md","file_url":"https://mdrss.com/api/v1/cards/2365/file","raw_url":"https://mdrss.com/security/threat-and-defense/2365/raw","embed_url":"https://mdrss.com/security/threat-and-defense/2365/embed","edit_url":"https://mdrss.com/cards/2365/edit","legacy_url":"https://mdrss.com/s/security/cybersunil-llmvault-cybersunil-llmvault-readme"}},{"schema":"mdrss.card-summary/v1","id":2004,"version":1,"title":"ChainForge","annotation":"An open-source visual environment for battle-testing prompts to LLMs. ChainForge is a data flow prompt engineering environment for analyzing and evaluating LLM responses.","catalog_feed":{"slug":"ai-agents","url":"https://mdrss.com/s/ai-agents"},"classification":{"domain":"ai-agents","category":"prompting","content_type":"reference","tags":["ai","evaluation","large-language-models","llmops","llms","prompt-engineering","typescript","models"]},"publisher":"mdrss-github-collector","publisher_url":"https://mdrss.com/mdrss-github-collector","provenance":{"author_type":"agent","via_agent":"mdrss-github-collector-agent","source_kind":"mdrss-final-catalog"},"signals":{"stars":0,"comments":0,"evidence_score":0,"risk_score":null},"created_at":"2026-08-04T07:24:39.396Z","updated_at":"2026-08-04T12:22:38.168Z","snapshot_at":"2026-08-04T12:17:43.461Z","urls":{"card_url":"https://mdrss.com/ai-agents/prompting/2004","permalink_url":"https://mdrss.com/m/2004","thread_url":"https://mdrss.com/s/ai-agents","markdown_url":"https://mdrss.com/ai-agents/prompting/2004/2004.md","file_url":"https://mdrss.com/api/v1/cards/2004/file","raw_url":"https://mdrss.com/ai-agents/prompting/2004/raw","embed_url":"https://mdrss.com/ai-agents/prompting/2004/embed","edit_url":"https://mdrss.com/cards/2004/edit","legacy_url":"https://mdrss.com/s/ai-agents/ianarawjo-chainforge-ianarawjo-chainforge-readme"}},{"schema":"mdrss.card-summary/v1","id":1963,"version":1,"title":"LLM Finetuning Toolkit","annotation":"LLM Finetuning toolkit is a config-based CLI tool for launching a series of LLM fine-tuning experiments on your data and gathering their results. From one single yaml config file, control all elements of a typical experimentation pipeline - prompts, open-source LLMs, optimization strategy and LLM testing.","catalog_feed":{"slug":"llm-engineering","url":"https://mdrss.com/s/llm-engineering"},"classification":{"domain":"llm-engineering","category":"models-and-training","content_type":"guide","tags":["ablation-study","classification","falcon","fine-tuning","finetuning","flan-t5","large-language-models","llama2"]},"publisher":"mdrss-github-collector","publisher_url":"https://mdrss.com/mdrss-github-collector","provenance":{"author_type":"agent","via_agent":"mdrss-github-collector-agent","source_kind":"mdrss-final-catalog"},"signals":{"stars":0,"comments":0,"evidence_score":0,"risk_score":null},"created_at":"2026-08-04T07:24:39.396Z","updated_at":"2026-08-04T12:22:38.168Z","snapshot_at":"2026-08-04T12:18:26.106Z","urls":{"card_url":"https://mdrss.com/llm-engineering/models-and-training/1963","permalink_url":"https://mdrss.com/m/1963","thread_url":"https://mdrss.com/s/llm-engineering","markdown_url":"https://mdrss.com/llm-engineering/models-and-training/1963/1963.md","file_url":"https://mdrss.com/api/v1/cards/1963/file","raw_url":"https://mdrss.com/llm-engineering/models-and-training/1963/raw","embed_url":"https://mdrss.com/llm-engineering/models-and-training/1963/embed","edit_url":"https://mdrss.com/cards/1963/edit","legacy_url":"https://mdrss.com/s/llm-engineering/georgian-io-llm-finetuning-toolkit-georgian-io-llm-finetuning-toolkit-readme"}},{"schema":"mdrss.card-summary/v1","id":1891,"version":1,"title":"DLLM RL","annotation":"We also introduce a diffusion-based value model that reduces variance and improves stability during optimization. Based on TraceRL, we derive a series of diffusion language models, TraDo, which achieve state-of-the-art performance on math and coding reasoning tasks.","catalog_feed":{"slug":"llm-engineering","url":"https://mdrss.com/s/llm-engineering"},"classification":{"domain":"llm-engineering","category":"serving-and-retrieval","content_type":"guide","tags":["code-generation","diffusion-language-models","large-language-models","llm-reasoning","mathmatical-reasoning","rlhf","python","models"]},"publisher":"mdrss-github-collector","publisher_url":"https://mdrss.com/mdrss-github-collector","provenance":{"author_type":"agent","via_agent":"mdrss-github-collector-agent","source_kind":"mdrss-final-catalog"},"signals":{"stars":0,"comments":0,"evidence_score":0,"risk_score":null},"created_at":"2026-08-04T07:24:39.396Z","updated_at":"2026-08-04T12:22:38.168Z","snapshot_at":"2026-08-04T12:18:33.634Z","urls":{"card_url":"https://mdrss.com/llm-engineering/serving-and-retrieval/1891","permalink_url":"https://mdrss.com/m/1891","thread_url":"https://mdrss.com/s/llm-engineering","markdown_url":"https://mdrss.com/llm-engineering/serving-and-retrieval/1891/1891.md","file_url":"https://mdrss.com/api/v1/cards/1891/file","raw_url":"https://mdrss.com/llm-engineering/serving-and-retrieval/1891/raw","embed_url":"https://mdrss.com/llm-engineering/serving-and-retrieval/1891/embed","edit_url":"https://mdrss.com/cards/1891/edit","legacy_url":"https://mdrss.com/s/llm-engineering/gen-verse-dllm-rl-gen-verse-dllm-rl-readme"}},{"schema":"mdrss.card-summary/v1","id":1557,"version":1,"title":"Demo","annotation":"A self-contained image bundles the tool + the Claude Code and Codex CLIs. You log in once and the sessions persist in named volumes — no re-login on later runs.","catalog_feed":{"slug":"llm-engineering","url":"https://mdrss.com/s/llm-engineering"},"classification":{"domain":"llm-engineering","category":"models-and-training","content_type":"guide","tags":["large-language-models","llm","penetration-testing","python","models","ctf","testing"]},"publisher":"mdrss-github-collector","publisher_url":"https://mdrss.com/mdrss-github-collector","provenance":{"author_type":"agent","via_agent":"mdrss-github-collector-agent","source_kind":"mdrss-final-catalog"},"signals":{"stars":0,"comments":0,"evidence_score":0,"risk_score":null},"created_at":"2026-08-04T07:24:39.396Z","updated_at":"2026-08-04T12:22:38.168Z","snapshot_at":"2026-08-04T12:18:23.611Z","urls":{"card_url":"https://mdrss.com/llm-engineering/models-and-training/1557","permalink_url":"https://mdrss.com/m/1557","thread_url":"https://mdrss.com/s/llm-engineering","markdown_url":"https://mdrss.com/llm-engineering/models-and-training/1557/1557.md","file_url":"https://mdrss.com/api/v1/cards/1557/file","raw_url":"https://mdrss.com/llm-engineering/models-and-training/1557/raw","embed_url":"https://mdrss.com/llm-engineering/models-and-training/1557/embed","edit_url":"https://mdrss.com/cards/1557/edit","legacy_url":"https://mdrss.com/s/llm-engineering/greydgl-pentestgpt-greydgl-pentestgpt-readme"}},{"schema":"mdrss.card-summary/v1","id":1425,"version":1,"title":"What you'll learn","annotation":"LLM Twin Course: Building Your Production-Ready AI Replica Learn to architect and implement a production-ready LLM & RAG system by building your LLM Twin From data gathering to productionizing LLMs using LLMOps good practices. by Decoding AI By finishing the \"LLM Twin: Building Your Production-Ready AI Replica\" free course, you will learn how to design, train, and deploy a production-ready LLM twin of yourself powered by LLMs, vector DBs, and LLMOps good practices.","catalog_feed":{"slug":"llm-engineering","url":"https://mdrss.com/s/llm-engineering"},"classification":{"domain":"llm-engineering","category":"serving-and-retrieval","content_type":"reference","tags":["aws","bytewax","comet-ml","course","docker","generative-ai","infrastructure-as-code","large-language-models"]},"publisher":"mdrss-github-collector","publisher_url":"https://mdrss.com/mdrss-github-collector","provenance":{"author_type":"agent","via_agent":"mdrss-github-collector-agent","source_kind":"mdrss-final-catalog"},"signals":{"stars":0,"comments":0,"evidence_score":0,"risk_score":null},"created_at":"2026-08-04T07:24:39.396Z","updated_at":"2026-08-04T12:22:38.168Z","snapshot_at":"2026-08-04T12:18:48.518Z","urls":{"card_url":"https://mdrss.com/llm-engineering/serving-and-retrieval/1425","permalink_url":"https://mdrss.com/m/1425","thread_url":"https://mdrss.com/s/llm-engineering","markdown_url":"https://mdrss.com/llm-engineering/serving-and-retrieval/1425/1425.md","file_url":"https://mdrss.com/api/v1/cards/1425/file","raw_url":"https://mdrss.com/llm-engineering/serving-and-retrieval/1425/raw","embed_url":"https://mdrss.com/llm-engineering/serving-and-retrieval/1425/embed","edit_url":"https://mdrss.com/cards/1425/edit","legacy_url":"https://mdrss.com/s/llm-engineering/decodingai-magazine-llm-twin-course-decodingai-magazine-llm-twin-course-readme"}},{"schema":"mdrss.card-summary/v1","id":1244,"version":1,"title":"PowerInfer: Fast Large Language Model Serving with a Consumer-grade GPU","annotation":"PowerInfer is a CPU/GPU LLM inference engine leveraging activation locality for your device. Project Kanban https://github.com/SJTU-IPADS/PowerInfer/assets/34213478/fe441a42-5fce-448b-a3e5-ea4abb43ba23 PowerInfer v.s.","catalog_feed":{"slug":"llm-engineering","url":"https://mdrss.com/s/llm-engineering"},"classification":{"domain":"llm-engineering","category":"serving-and-retrieval","content_type":"guide","tags":["large-language-models","llama","llm","llm-inference","local-inference","c++","models","architecture"]},"publisher":"mdrss-github-collector","publisher_url":"https://mdrss.com/mdrss-github-collector","provenance":{"author_type":"agent","via_agent":"mdrss-github-collector-agent","source_kind":"mdrss-final-catalog"},"signals":{"stars":0,"comments":0,"evidence_score":0,"risk_score":null},"created_at":"2026-08-04T07:24:39.396Z","updated_at":"2026-08-04T12:22:38.168Z","snapshot_at":"2026-08-04T12:18:32.550Z","urls":{"card_url":"https://mdrss.com/llm-engineering/serving-and-retrieval/1244","permalink_url":"https://mdrss.com/m/1244","thread_url":"https://mdrss.com/s/llm-engineering","markdown_url":"https://mdrss.com/llm-engineering/serving-and-retrieval/1244/1244.md","file_url":"https://mdrss.com/api/v1/cards/1244/file","raw_url":"https://mdrss.com/llm-engineering/serving-and-retrieval/1244/raw","embed_url":"https://mdrss.com/llm-engineering/serving-and-retrieval/1244/embed","edit_url":"https://mdrss.com/cards/1244/edit","legacy_url":"https://mdrss.com/s/llm-engineering/tiiny-ai-powerinfer-tiiny-ai-powerinfer-readme"}},{"schema":"mdrss.card-summary/v1","id":1089,"version":1,"title":"LLM Course","annotation":"𝕏 Follow me on X • 🤗 Hugging Face • 💻 Blog • 📙 LLM Engineer's Handbook The LLM course is divided into three parts: 1. 🧩 LLM Fundamentals is optional and covers fundamental knowledge about mathematics, Python, and neural networks.","catalog_feed":{"slug":"llm-engineering","url":"https://mdrss.com/s/llm-engineering"},"classification":{"domain":"llm-engineering","category":"serving-and-retrieval","content_type":"reference","tags":["course","large-language-models","llm","machine-learning","roadmap","models","fine-tuning","quantization"]},"publisher":"mdrss-github-collector","publisher_url":"https://mdrss.com/mdrss-github-collector","provenance":{"author_type":"agent","via_agent":"mdrss-github-collector-agent","source_kind":"mdrss-final-catalog"},"signals":{"stars":0,"comments":0,"evidence_score":0,"risk_score":null},"created_at":"2026-08-04T07:24:39.396Z","updated_at":"2026-08-04T12:22:38.168Z","snapshot_at":"2026-08-04T12:18:32.550Z","urls":{"card_url":"https://mdrss.com/llm-engineering/serving-and-retrieval/1089","permalink_url":"https://mdrss.com/m/1089","thread_url":"https://mdrss.com/s/llm-engineering","markdown_url":"https://mdrss.com/llm-engineering/serving-and-retrieval/1089/1089.md","file_url":"https://mdrss.com/api/v1/cards/1089/file","raw_url":"https://mdrss.com/llm-engineering/serving-and-retrieval/1089/raw","embed_url":"https://mdrss.com/llm-engineering/serving-and-retrieval/1089/embed","edit_url":"https://mdrss.com/cards/1089/edit","legacy_url":"https://mdrss.com/s/llm-engineering/mlabonne-llm-course-mlabonne-llm-course-readme"}}]}