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Merge mainline llama.cpp (#3)
* Merging mainline - WIP * Merging mainline - WIP AVX2 and CUDA appear to work. CUDA performance seems slightly (~1-2%) lower as it is so often the case with llama.cpp/ggml after some "improvements" have been made. * Merging mainline - fix Metal * Remove check --------- Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
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@@ -6,12 +6,11 @@ Apply LORA adapters to base model and export the resulting model.
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usage: llama-export-lora [options]
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options:
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-h, --help show this help message and exit
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-m FNAME, --model-base FNAME model path from which to load base model (default '')
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-o FNAME, --model-out FNAME path to save exported model (default '')
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-l FNAME, --lora FNAME apply LoRA adapter
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-s FNAME S, --lora-scaled FNAME S apply LoRA adapter with user defined scaling S
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-t N, --threads N number of threads to use during computation (default: 4)
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-m, --model model path from which to load base model (default '')
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--lora FNAME path to LoRA adapter (can be repeated to use multiple adapters)
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--lora-scaled FNAME S path to LoRA adapter with user defined scaling S (can be repeated to use multiple adapters)
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-t, --threads N number of threads to use during computation (default: 4)
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-o, --output FNAME output file (default: 'ggml-lora-merged-f16.gguf')
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```
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For example:
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@@ -20,7 +19,15 @@ For example:
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./bin/llama-export-lora \
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-m open-llama-3b-v2-q8_0.gguf \
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-o open-llama-3b-v2-q8_0-english2tokipona-chat.gguf \
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-l lora-open-llama-3b-v2-q8_0-english2tokipona-chat-LATEST.bin
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--lora lora-open-llama-3b-v2-q8_0-english2tokipona-chat-LATEST.gguf
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```
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Multiple LORA adapters can be applied by passing multiple `-l FN` or `-s FN S` command line parameters.
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Multiple LORA adapters can be applied by passing multiple `--lora FNAME` or `--lora-scaled FNAME S` command line parameters:
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```bash
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./bin/llama-export-lora \
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-m your_base_model.gguf \
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-o your_merged_model.gguf \
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--lora-scaled lora_task_A.gguf 0.5 \
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--lora-scaled lora_task_B.gguf 0.5
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```
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