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* `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>
28 lines
971 B
Markdown
28 lines
971 B
Markdown
# train-text-from-scratch
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Basic usage instructions:
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```bash
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# get training data
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wget https://raw.githubusercontent.com/brunoklein99/deep-learning-notes/master/shakespeare.txt
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# train
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./bin/llama-train-text-from-scratch \
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--vocab-model ../models/ggml-vocab-llama.gguf \
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--ctx 64 --embd 256 --head 8 --layer 16 \
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--checkpoint-in chk-shakespeare-256x16-LATEST.gguf \
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--checkpoint-out chk-shakespeare-256x16-ITERATION.gguf \
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--model-out ggml-shakespeare-256x16-f32-ITERATION.gguf \
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--train-data "shakespeare.txt" \
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-t 6 -b 16 --seed 1 --adam-iter 256 \
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--no-checkpointing
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# predict
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./bin/llama-cli -m ggml-shakespeare-256x16-f32.gguf
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```
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Output files will be saved every N iterations (config with `--save-every N`).
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The pattern "ITERATION" in the output filenames will be replaced with the iteration number and "LATEST" for the latest output.
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To train GGUF models just pass them to `--checkpoint-in FN`.
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