A simulation of me: fine-tuning an LLM on 240k text messages

• nanoGPT

  69 31,914 5.4 Python

  The simplest, fastest repository for training/finetuning medium-sized GPTs.

This repo, albeit "old" in regards to how much progress there's been in LLMs, has great simple tutorials right there eg. fine-tuning GPT2 with Shakespeare: https://github.com/karpathy/nanoGPT

• llama.cpp

  773 56,891 10.0 C++

  LLM inference in C/C++

https://github.com/ggerganov/llama.cpp/pull/1684

You are broadly better off running a larger, more quantized model, than a smaller model at a higher precision. A 65b parameter model with 2bit quantization still outperforms a 30b parameter model in perplexity.

People train LoRAs at low precision regularly. The folks on /r/localllama are really pushing the boundaries of what can be done on consumer hardware, and the boundaries are further out than you'd think.

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

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