LLMs-from-scratch
rest.li
LLMs-from-scratch | rest.li | |
---|---|---|
11 | 2 | |
19,418 | 2,444 | |
- | 0.3% | |
9.6 | 8.3 | |
about 17 hours ago | 6 days ago | |
Jupyter Notebook | Java | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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LLMs-from-scratch
- Evaluating LLMs locally, on a laptop, with Llama 3 and Ollama
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Ask HN: What are some books/resources where we can learn by building
By happenchance today I learned that Manning recently started working on publishing a X From Scratch series, which currently includes:
* Container Orchestrator: https://www.manning.com/books/build-an-orchestrator-in-go-fr...
* LLM : https://www.manning.com/books/build-a-large-language-model-f...
* Frontend Framework: https://www.manning.com/books/build-a-frontend-web-framework...
- Finetuning an LLM-Based Spam Classifier with LoRA from Scratch
- Finetune a GPT Model for Spam Detection on Your Laptop in Just 5 Minutes
- Insights from Finetuning LLMs for Classification Tasks
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Ask HN: Textbook Regarding LLMs
https://www.manning.com/books/build-a-large-language-model-f...
- Comparing 5 ways to implement Multihead Attention in PyTorch
- FLaNK Stack 29 Jan 2024
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Implementing a ChatGPT-like LLM from scratch, step by step
The attention mechanism we implement in this book* is specific to LLMs in terms of the text inputs, but it's fundamentally the same attention mechanism that is used in vision transformers. The only difference is that in LLMs, you turn text into tokens, and convert these tokens into vector embeddings that go into an LLM. In vision transformers, instead of regarding images as tokens, you use an image patch as a token and turn those into vector embeddings (a bit hard to explain without visuals here). In both text or vision context, it's the same attention mechanism, and it both cases it receives vector embeddings.
(*Chapter 3, already submitted last week and should be online in the MEAP soon, in the meantime the code along with the notes is also available here: https://github.com/rasbt/LLMs-from-scratch/blob/main/ch03/01...)
rest.li
- FLaNK Stack 29 Jan 2024
-
LinkedIn Adopts Protocol Buffers and Reduces Latency Up to 60%
From rest.li's github page[0] -
At LinkedIn, we are focusing our efforts on advanced automation to enable a seamless, LinkedIn-wide migration from Rest.li to gRPC. gRPC will offer better performance, support for more programming languages, streaming, and a robust open source community. There is no active development at LinkedIn on new features for Rest.li. The repository will also be deprecated soon once we have migrated services to use gRPC. Refer to this blog[1] for more details on why we are moving to gRPC.
[0] - https://github.com/linkedin/rest.li
[1] - https://engineering.linkedin.com/blog/2023/linkedin-integrat...
What are some alternatives?
s4 - Structured state space sequence models
Swagger - The content of swagger.io
Feign - Feign makes writing java http clients easier
Jersey - Eclipse Jersey Project - Read our Wiki:
Dropwizard - A damn simple library for building production-ready RESTful web services.
Retrofit - A type-safe HTTP client for Android and the JVM
Microserver - Microserver is a Java 8 native, zero configuration, standards based, battle hardened library to run Java Rest Microservices via a standard Java main class. Supporting pure Microservice or Micro-monolith styles.
Restlet Framework - The first REST API framework for Java
Restler - Restler is a library that automatically generates a client for a web service at run time, by analyzing the respective annotated Spring controller interface
RestExpress - Minimalist Java framework for rapidly creating scalable, containerless, RESTful microservices. Ship a production-quality, headless, RESTful API in the shortest time possible. Uses Netty for HTTP, Jackson for JSON, Metrics for metrics, properties files for configuration. Sub-projects and plugins enable, NoSQL, Swagger, Auth0, HAL integration, etc.
RESTEasy - An Implementation of the Jakarta RESTful Web Services Specification
Rapidoid - Rapidoid - Extremely Fast, Simple and Powerful Java Web Framework and HTTP Server!