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koboldcpp/examples/export-lora
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Concedo e8de0af3ec Merge branch 'upstream' into concedo_experimental 
# Conflicts:
#	.github/workflows/bench.yml
#	.github/workflows/build.yml
#	.github/workflows/python-check-requirements.yml
#	README.md
#	docs/backend/SYCL.md
#	flake.lock
#	ggml/CMakeLists.txt
#	ggml/src/kompute-shaders/op_rope_f16.comp
#	ggml/src/kompute-shaders/op_rope_f32.comp
#	ggml/src/kompute-shaders/rope_common.comp
2024-08-14 22:25:43 +08:00
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export-lora.cpp export-lora : throw error if lora is quantized (#9002) 2024-08-13 11:41:14 +02:00
README.md export-lora : throw error if lora is quantized (#9002) 2024-08-13 11:41:14 +02:00

README.md

export-lora

Apply LORA adapters to base model and export the resulting model.

usage: llama-export-lora [options]

options:
  -m,    --model                  model path from which to load base model (default '')
         --lora FNAME             path to LoRA adapter  (can be repeated to use multiple adapters)
         --lora-scaled FNAME S    path to LoRA adapter with user defined scaling S  (can be repeated to use multiple adapters)
  -t,    --threads N              number of threads to use during computation (default: 4)
  -o,    --output FNAME           output file (default: 'ggml-lora-merged-f16.gguf')

For example:

./bin/llama-export-lora \
    -m open-llama-3b-v2.gguf \
    -o open-llama-3b-v2-english2tokipona-chat.gguf \
    --lora lora-open-llama-3b-v2-english2tokipona-chat-LATEST.gguf

Multiple LORA adapters can be applied by passing multiple --lora FNAME or --lora-scaled FNAME S command line parameters:

./bin/llama-export-lora \
    -m your_base_model.gguf \
    -o your_merged_model.gguf \
    --lora-scaled lora_task_A.gguf 0.5 \
    --lora-scaled lora_task_B.gguf 0.5