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History

Olivier Chafik 1c641e6aac `build`: rename main → llama-cli, server → llama-server, llava-cli → llama-llava-cli, etc... (#7809 ) * `main`/`server`: rename to `llama` / `llama-server` for consistency w/ homebrew * server: update refs -> llama-server gitignore llama-server * server: simplify nix package * main: update refs -> llama fix examples/main ref * main/server: fix targets * update more names * Update build.yml * rm accidentally checked in bins * update straggling refs * Update .gitignore * Update server-llm.sh * main: target name -> llama-cli * Prefix all example bins w/ llama- * fix main refs * rename {main->llama}-cmake-pkg binary * prefix more cmake targets w/ llama- * add/fix gbnf-validator subfolder to cmake * sort cmake example subdirs * rm bin files * fix llama-lookup-* Makefile rules * gitignore /llama-* * rename Dockerfiles * rename llama\|main -> llama-cli; consistent RPM bin prefixes * fix some missing -cli suffixes * rename dockerfile w/ llama-cli * rename(make): llama-baby-llama * update dockerfile refs * more llama-cli(.exe) * fix test-eval-callback * rename: llama-cli-cmake-pkg(.exe) * address gbnf-validator unused fread warning (switched to C++ / ifstream) * add two missing llama- prefixes * Updating docs for eval-callback binary to use new `llama-` prefix. * Updating a few lingering doc references for rename of main to llama-cli * Updating `run-with-preset.py` to use new binary names. Updating docs around `perplexity` binary rename. * Updating documentation references for lookup-merge and export-lora * Updating two small `main` references missed earlier in the finetune docs. * Update apps.nix * update grammar/README.md w/ new llama-* names * update llama-rpc-server bin name + doc * Revert "update llama-rpc-server bin name + doc" This reverts commit `e474ef1df4`. * add hot topic notice to README.md * Update README.md * Update README.md * rename gguf-split & quantize bins refs in **/tests.sh --------- Co-authored-by: HanClinto <hanclinto@gmail.com>		2024-06-13 00:41:52 +01:00
..
CMakeLists.txt	`build`: rename main → llama-cli, server → llama-server, llava-cli → llama-llava-cli, etc... (#7809 )	2024-06-13 00:41:52 +01:00
convert-train-checkpoint-to-gguf.py	gguf-py: Refactor and allow reading/modifying existing GGUF files (#3981 )	2023-11-11 08:04:50 +03:00
README.md	`build`: rename main → llama-cli, server → llama-server, llava-cli → llama-llava-cli, etc... (#7809 )	2024-06-13 00:41:52 +01:00
train-text-from-scratch.cpp	ggml : refactor rope norm/neox (#7634 )	2024-06-05 11:29:20 +03:00

README.md

train-text-from-scratch

Basic usage instructions:

# get training data
wget https://raw.githubusercontent.com/brunoklein99/deep-learning-notes/master/shakespeare.txt

# train
./bin/llama-train-text-from-scratch \
        --vocab-model ../models/ggml-vocab-llama.gguf \
        --ctx 64 --embd 256 --head 8 --layer 16 \
        --checkpoint-in  chk-shakespeare-256x16-LATEST.gguf \
        --checkpoint-out chk-shakespeare-256x16-ITERATION.gguf \
        --model-out ggml-shakespeare-256x16-f32-ITERATION.gguf \
        --train-data "shakespeare.txt" \
        -t 6 -b 16 --seed 1 --adam-iter 256 \
        --no-checkpointing

# predict
./bin/llama-cli -m ggml-shakespeare-256x16-f32.gguf

Output files will be saved every N iterations (config with --save-every N). The pattern "ITERATION" in the output filenames will be replaced with the iteration number and "LATEST" for the latest output.

To train GGUF models just pass them to --checkpoint-in FN.