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201cc11afa
* add phi3 128k support in convert-hf-to-gguf * add phi3 128k support in cuda * address build warnings on llama.cpp * adjust index value in cuda long rope freq factors * add long rope support in ggml cpu backend * make freq factors only depend on ctx size * remove unused rope scaling type 'su' frin gguf converter * fix flint warnings on convert-hf-to-gguf.py * set to the short freq factor when context size is small than trained context size * add one line of comments * metal : support rope freq_factors * ggml : update ggml_rope_ext API to support freq. factors * backends : add dev messages to support rope freq. factors * minor : style * tests : update to use new rope API * backends : fix pragma semicolons * minor : cleanup * llama : move rope factors from KV header to tensors * llama : remove tmp assert * cuda : fix compile warning * convert : read/write n_head_kv * llama : fix uninitialized tensors --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> |
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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.