LLMs
LLM-PowerHouse: A Curated Guide for Large Language Models with Custom Training and Inferencing
Welcome to LLM-PowerHouse, your ultimate resource for unleashing the full potential of Large Language Models (LLMs) with custom training and inferencing. This GitHub repository is a comprehensive and curated guide designed to empower developers,... See more
Welcome to LLM-PowerHouse, your ultimate resource for unleashing the full potential of Large Language Models (LLMs) with custom training and inferencing. This GitHub repository is a comprehensive and curated guide designed to empower developers,... See more
ghimiresunil • GitHub - ghimiresunil/LLM-PowerHouse-A-Curated-Guide-for-Large-Language-Models-with-Custom-Training-and-Inferencing: LLM-PowerHouse: Unleash LLMs' potential through curated tutorials, best practices, and ready-to-use code for custom training and inferencing.
First time here? Go to our setup guide
Features
Features
- 🤖 Multiple model integrations: OpenAI, transformers, llama.cpp, exllama2, mamba
- 🖍️ Simple and powerful prompting primitives based on the Jinja templating engine
- 🚄 Multiple choices, type constraints and dynamic stopping
- ⚡ Fast regex-structured generation
- 🔥 Fast JSON generation following a JSON schema
outlines-dev • GitHub - outlines-dev/outlines: Neuro Symbolic Text Generation
Take a look at our official page for user documentation and examples: langtest.org
Key Features
Key Features
- Generate and execute more than 50 distinct types of tests only with 1 line of code
- Test all aspects of model quality: robustness, bias, representation, fairness and accuracy.
- Automatically augment training data based on test results (for select models)
- Sup
GitHub - BrunoScaglione/langtest: Deliver safe & effective language models
What’s the best way for an end user to organize and explore millions of latent space features?
I’ve found tens of thousands of interpretable features in my experiments, and frontier labs have demonstrated results with a thousand times more features in production-scale models. No doubt, as interpretability techniques advance, we’ll see feature maps... See more
I’ve found tens of thousands of interpretable features in my experiments, and frontier labs have demonstrated results with a thousand times more features in production-scale models. No doubt, as interpretability techniques advance, we’ll see feature maps... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
📦 Service Deployment - Ray Serve (https://lnkd.in/eAV-Y6RN)
🧰 Data Transformation - Ray Data (https://lnkd.in/e7wYmenc)
🔌 LLM Integration - AIConfig (https://lnkd.in/esvH5NQa)
🗄 Vector Database - Weaviate (https://weaviate.io/)
📚 Supervised LLM Fine-Tuning - HuggingFace TLR (https://lnkd.in/e8_QYF-P)
📈 LLM Observability - Weights & Biases Traces (https... See more
🧰 Data Transformation - Ray Data (https://lnkd.in/e7wYmenc)
🔌 LLM Integration - AIConfig (https://lnkd.in/esvH5NQa)
🗄 Vector Database - Weaviate (https://weaviate.io/)
📚 Supervised LLM Fine-Tuning - HuggingFace TLR (https://lnkd.in/e8_QYF-P)
📈 LLM Observability - Weights & Biases Traces (https... See more
Paul Venuto • feed updates
OpenAI is treating its new marketplace seriously now: The brand new GPT store will come with REVENUE SHARING.... (missing in the Plugins launch)
and launching a Stateful Assistants API:
- Persistent Threads (/api/openai/threads)
- Built in Retrieval (chunking etc done for you)
- Code Interpreter (RIP Adv Data Analysis?)
- Speech to Text and Text to... See more
and launching a Stateful Assistants API:
- Persistent Threads (/api/openai/threads)
- Built in Retrieval (chunking etc done for you)
- Code Interpreter (RIP Adv Data Analysis?)
- Speech to Text and Text to... See more
swyx • Tweet
Today, we’re releasing the Assistants API, our first step towards helping developers build agent-like experiences within their own applications. An assistant is a purpose-built AI that has specific instructions, leverages extra knowledge, and can call models and tools to perform tasks. The new Assistants API provides new capabilities such as Code... See more
New models and developer products announced at DevDay
- Self-play is the idea that an agent can improve its gameplay by playing against slightly different versions of itself because it’ll progressively encounter more challenging situations. In the space of LLMs, it is almost certain that the largest portion of self-play will look like AI Feedback rather than competitive processes.
Nathan Lambert • The Q* hypothesis: Tree-of-thoughts reasoning, process reward models, and supercharging synthetic data
🤖 Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
- Why CrewAI
- Getting Started
- Key Features
- Examples
- Local Open Source Models
- CrewAI x AutoGen x ChatDev
- Contribution
- 💬 CrewAI Discord Community
- Hire Consulting
- License