There several places where a gguf context is allocated. A call to gguf_free is missing in some error paths. Also on linux, llama-bench was missing a fclose. |
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.. | ||
CMakeLists.txt | ||
convert-train-checkpoint-to-gguf.py | ||
README.md | ||
train-text-from-scratch.cpp |
train-text-from-scratch
Basic usage instructions:
# get training data
wget https://raw.githubusercontent.com/brunoklein99/deep-learning-notes/master/shakespeare.txt
# train
./bin/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/main -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
.