--- layout: default title: Learn nav_order: 4 has_children: true description: key learning resources permalink: /learn --- Learn: Youtube Video Series --- **Tutorial Videos** - check out our Youtube channel for high-impact 5-10 minute tutorials on the latest examples. Check back often as this list is always growing ... 🎬 **Some of our most recent videos** - [Best Small RAG Model - Bling-Phi-3](https://youtu.be/cViMonCAeSc?si=L6jX0sRdZAmKtRcz) - [Agent Automation with Web Services for Financial Research](https://youtu.be/l0jzsg1_Ik0?si=oBGtALHLplouY9x2) - [Voice Transcription and Automated Analysis of Greatest Speeches Dataset](https://youtu.be/5y0ez5ZBpPE?si=PAaCIqYou8nCGxYG) - [Are you prompting wrong for RAG - Stochastic Sampling-Part I](https://youtu.be/7oMTGhSKuNY?si=_KSjuBnqArvWzYbx) - [Are you prompting wrong for RAG - Stochastic Sampling-Part II- Code Experiments](https://youtu.be/iXp1tj-pPjM?si=3ZeMgipY0vJDHIMY) 🎬 **Using Agents, Function Calls and SLIM models** - [SLIMS Playlist](https://youtube.com/playlist?list=PL1-dn33KwsmAHWCWK6YjZrzicQ2yR6W8T&si=TSFGqQ3ObOO5vDde) - [Agent-based Complex Research Analysis](https://youtu.be/y4WvwHqRR60?si=jX3KCrKcYkM95boe) - [Getting Started with SLIMs (with code)](https://youtu.be/aWZFrTDmMPc?si=lmo98_quo_2Hrq0C) - [SLIM Models Intro](https://www.youtube.com/watch?v=cQfdaTcmBpY) - [Text2SQL Intro](https://youtu.be/BKZ6kO2XxNo?si=tXGt63pvrp_rOlIP) - [Pop up LLMWare Inference Server](https://www.youtube.com/watch?v=qiEmLnSRDUA&t=20s) - [Hardest Problem in RAG - handling 'Not Found'](https://youtu.be/slDeF7bYuv0?si=j1nkdwdGr5sgvUtK) - [Extract Information from Earnings Releases](https://youtu.be/d6HFfyDk4YE?si=VmnIiWFmgBtR4DxS) - [Summary Function Calls](https://youtu.be/yNg_KH5cPSk?si=Yl94tp_vKA8e7eT7) - [Boolean Yes-No Function Calls](https://youtu.be/jZQZMMqAJXs?si=lU4YVI0H0tfc9k6e) - [Autogenerate Topics, Tags and NER](https://youtu.be/N6oOxuyDsC4?si=vo2Fd8VG5xTbH4SD) 🎬 **Using GGUF Models** - [Using LM Studio Models](https://www.youtube.com/watch?v=h2FDjUyvsKE) - [Using Ollama Models](https://www.youtube.com/watch?v=qITahpVDuV0) - [Use any GGUF Model](https://www.youtube.com/watch?v=9wXJgld7Yow) - [Background on GGUF Quantization & DRAGON Model Example](https://www.youtube.com/watch?v=ZJyQIZNJ45E) - [Getting Started with Whisper.CPP](https://youtu.be/YG5u5AOU9MQ?si=5xQYZCILPSiR8n4s) 🎬 **Core RAG Scenarios Running Locally** - [RAG with BLING on your laptop](https://www.youtube.com/watch?v=JjgqOZ2v5oU) - [DRAGON-7B-Models](https://www.youtube.com/watch?v=d_u7VaKu6Qk&t=37s) - [Use small LLMs for RAG for Contract Analysis (feat. LLMWare)](https://www.youtube.com/watch?v=8aV5p3tErP0) - [Invoice Processing with LLMware](https://www.youtube.com/watch?v=VHZSaBBG-Bo&t=10s) - [Evaluate LLMs for RAG with LLMWare](https://www.youtube.com/watch?v=s0KWqYg5Buk&t=105s) - [Fast Start to RAG with LLMWare Open Source Library](https://www.youtube.com/watch?v=0naqpH93eEU) - [Use Retrieval Augmented Generation (RAG) without a Database](https://www.youtube.com/watch?v=tAGz6yR14lw) 🎬 **Parsing, Embedding, Data Pipelines and Extraction** - [Ingest PDFs at Scale](https://www.youtube.com/watch?v=O0adUfrrxi8&t=10s) - [Install and Compare Multiple Embeddings with Postgres and PGVector](https://www.youtube.com/watch?v=Bncvggy6m5Q) - [Intro to Parsing and Text Chunking](https://youtu.be/2xDefZ4oBOM?si=YZzBUjDfQ0839EVF) # More information about the project - [see main repository](https://www.github.com/llmware-ai/llmware.git) # About the project `llmware` is © 2023-{{ "now" | date: "%Y" }} by [AI Bloks](https://www.aibloks.com/home). ## Contributing Please first discuss any change you want to make publicly, for example on GitHub via raising an [issue](https://github.com/llmware-ai/llmware/issues) or starting a [new discussion](https://github.com/llmware-ai/llmware/discussions). You can also write an email or start a discussion on our Discrod channel. Read more about becoming a contributor in the [GitHub repo](https://github.com/llmware-ai/llmware/blob/main/CONTRIBUTING.md). ## Code of conduct We welcome everyone into the ``llmware`` community. [View our Code of Conduct](https://github.com/llmware-ai/llmware/blob/main/CODE_OF_CONDUCT.md) in our GitHub repository. ## ``llmware`` and [AI Bloks](https://www.aibloks.com/home) ``llmware`` is an open source project from [AI Bloks](https://www.aibloks.com/home) - the company behind ``llmware``. The company offers a Software as a Service (SaaS) Retrieval Augmented Generation (RAG) service. [AI Bloks](https://www.aibloks.com/home) was founded by [Namee Oberst](https://www.linkedin.com/in/nameeoberst/) and [Darren Oberst](https://www.linkedin.com/in/darren-oberst-34a4b54/) in October 2022. ## License `llmware` is distributed by an [Apache-2.0 license](https://www.github.com/llmware-ai/llmware/blob/main/LICENSE). ## Thank you to the contributors of ``llmware``! --- ---