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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true,
"id": "cmjOVVtJdiPZ"
},
"outputs": [],
"source": [
"!git clone https://github.com/cg123/mergekit.git\n",
"%cd mergekit\n",
"%pip install -e ."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"id": "84cRJT6_ecbw"
},
"outputs": [],
"source": [
"OUTPUT_PATH = \"./merged\" # folder to store the result in\n",
"LORA_MERGE_CACHE = \"/tmp\" # change if you want to keep these for some reason\n",
"CONFIG_YML = \"./examples/gradient-slerp.yml\" # merge configuration file\n",
"COPY_TOKENIZER = True # you want a tokenizer? yeah, that's what i thought\n",
"LAZY_UNPICKLE = False # experimental low-memory model loader\n",
"LOW_CPU_MEMORY = False # enable if you somehow have more VRAM than RAM+swap"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "6nw26xQLkBax"
},
"outputs": [],
"source": [
"# actually do merge\n",
"import torch\n",
"import yaml\n",
"\n",
"from mergekit.config import MergeConfiguration\n",
"from mergekit.merge import MergeOptions, run_merge\n",
"\n",
"with open(CONFIG_YML, \"r\", encoding=\"utf-8\") as fp:\n",
" merge_config = MergeConfiguration.model_validate(yaml.safe_load(fp))\n",
"\n",
"run_merge(\n",
" merge_config,\n",
" out_path=OUTPUT_PATH,\n",
" options=MergeOptions(\n",
" lora_merge_cache=LORA_MERGE_CACHE,\n",
" cuda=torch.cuda.is_available(),\n",
" copy_tokenizer=COPY_TOKENIZER,\n",
" lazy_unpickle=LAZY_UNPICKLE,\n",
" low_cpu_memory=LOW_CPU_MEMORY,\n",
" ),\n",
")\n",
"print(\"Done!\")"
]
}
],
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"gpuType": "T4",
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
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"file_extension": ".py",
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