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koboldcpp/examples/train-text-from-scratch
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Concedo 5b605d03ea Merge branch 'upstream' into concedo_experimental 
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convert_train_checkpoint_to_gguf.py py : switch to snake_case (#8305) 2024-07-05 07:53:33 +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.