{
"cells": [
{
"cell_type": "markdown",
"id": "bcec4157",
"metadata": {},
"source": [
"## AI disclosure\n",
"\n",
"This file was created after extensive troubleshooting during the process of converting our merged model into GGUF format. With assistance from ChatGPT, we were able to identify and resolve several issues encountered along the way. This notebook documents a complete and functional workflow for downloading our merged FP16 model from Hugging Face and converting it into a GGUF version suitable for CPU inference using tools such as llama.cpp or GPT4All."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "OhVfpxc9aOI6",
"metadata": {
"id": "OhVfpxc9aOI6",
"scrolled": true
},
"outputs": [],
"source": [
"%%capture\n",
"%uv pip install unsloth\n",
"# Also get the latest nightly Unsloth!\n",
"%uv pip uninstall unsloth -y && pip install --upgrade --no-cache-dir --no-deps git+https://github.com/unslothai/unsloth.git@nightly git+https://github.com/unslothai/unsloth-zoo.git"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "wyQnJBfRbJI0",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 427,
"referenced_widgets": [
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},
"id": "wyQnJBfRbJI0",
"outputId": "4a372ff3-4c75-46c5-f774-b94074f1f117"
},
"outputs": [],
"source": [
"from huggingface_hub import snapshot_download\n",
"\n",
"local_model = snapshot_download(\n",
" repo_id=\"Jeppcode/ScalableLab2\",\n",
" allow_patterns=[\"merged-model-fp16/*\"]\n",
")\n",
"\n",
"print(local_model)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "psdEuTZYbk7T",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "psdEuTZYbk7T",
"outputId": "72d9bc87-552d-4c34-ea9a-627e737d65fa"
},
"outputs": [],
"source": [
"import os\n",
"\n",
"for root, dirs, files in os.walk(local_model, topdown=True):\n",
" for name in files:\n",
" print(os.path.join(root, name))\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "va9jTif9buop",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "va9jTif9buop",
"outputId": "cb72da58-87e2-4476-a67c-a79633c3e71c"
},
"outputs": [],
"source": [
"!pip install sentencepiece\n",
"!pip install huggingface_hub\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "TNf9JQGTby87",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "TNf9JQGTby87",
"outputId": "8c960658-b5a6-446a-8606-e22de4046216"
},
"outputs": [],
"source": [
"!git clone https://github.com/ggerganov/llama.cpp\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ZUbWFNJEb8ST",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "ZUbWFNJEb8ST",
"outputId": "198af464-da31-4b4c-9e29-8476fc6469de"
},
"outputs": [],
"source": [
"%cd llama.cpp\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "W0IV8Ep7b-2O",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "W0IV8Ep7b-2O",
"outputId": "d79fd308-f1d9-482b-d0c3-5fffbe6029ee"
},
"outputs": [],
"source": [
"HF_MODEL_PATH = \"/root/.cache/huggingface/hub/models--Jeppcode--ScalableLab2/snapshots/95c561c6ea6eb2d76c5691d6b4dd2dcbc533da7f/merged-model-fp16\"\n",
"\n",
"!python convert_hf_to_gguf.py \\\n",
" --outtype f16 \\\n",
" --outfile /content/model-f16.gguf \\\n",
" $HF_MODEL_PATH\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "zMqdZGtFct6o",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "zMqdZGtFct6o",
"outputId": "f42b73eb-3e9b-4432-cce3-9be34d1673c8"
},
"outputs": [],
"source": [
"%cd /content/llama.cpp\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "De_qnFZocxGr",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "De_qnFZocxGr",
"outputId": "7cc50a7b-9d43-4dc1-8bc7-62cee1f0a2d9"
},
"outputs": [],
"source": [
"!mkdir build\n",
"%cd build"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ddcZKYfUc8bi",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "ddcZKYfUc8bi",
"outputId": "821530b2-ac1b-4139-daf3-e96d4db60178"
},
"outputs": [],
"source": [
"!cmake .."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "hqoVmLt1dACt",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "hqoVmLt1dACt",
"outputId": "d61153ac-d640-46ec-bbc9-83e1e64f4a4c"
},
"outputs": [],
"source": [
"!cmake --build . --config Release\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "krACJhcufiyV",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "krACJhcufiyV",
"outputId": "78c1ec5a-0cee-4ba3-9b6f-2fcee2ad4a05"
},
"outputs": [],
"source": [
"!find /content/llama.cpp -type f -name \"quantize*\"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "K_21YyejfzKV",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "K_21YyejfzKV",
"outputId": "f6177c88-5748-4935-9e20-4cb9e5940a31"
},
"outputs": [],
"source": [
"!cmake --build . --config Release -t llama-quantize"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "AKLHye8If16y",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "AKLHye8If16y",
"outputId": "cf1be2eb-f18f-4389-9c49-25ce67249217"
},
"outputs": [],
"source": [
"!find /content/llama.cpp/build -type f -name \"llama-quantize\""
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "WiO50Milf8EV",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "WiO50Milf8EV",
"outputId": "bc2952a7-34a7-497f-b6e9-bafad75fcf94"
},
"outputs": [],
"source": [
"!\"/content/llama.cpp/build/bin/llama-quantize\" \\\n",
" /content/model-f16.gguf \\\n",
" /content/model-q4_k_m.gguf \\\n",
" q4_K_M"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "BI9svp8QhQNy",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "BI9svp8QhQNy",
"outputId": "a93cb43f-5176-4406-f4dc-d5900daf844b"
},
"outputs": [],
"source": [
"!ls -lh /content | grep gguf"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6THrnXFVkAA-",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 17,
"referenced_widgets": [
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"d0dc7009ccd647baa8cd56dca5c12acf",
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"015e111ca70647fb8a9cbf48ad314238",
"a22e75922e774b21b68acfb9bb96be31",
"9c56e415199a467899090e0a63d03a30",
"fbfa8ea0d7904b9e895a33a8b4bddd8b"
]
},
"id": "6THrnXFVkAA-",
"outputId": "5b289ca0-3f00-4da9-fd59-41a776d081c5"
},
"outputs": [],
"source": [
"\n",
"from huggingface_hub import login\n",
"login()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3pj_4Eb2kU6A",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 226,
"referenced_widgets": [
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"a0c858b2c7f2461680a8e70634c51450",
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"d6e60f14a67b43f5acf1d0b52471d4e0",
"eca4497ade864088bad5af21c81e1bb7",
"7685dc179cf2439f83b6fdfca734a801",
"6997f24a6da248d5935eaa3f320767a7",
"3c8b4256beb34137b0a517b9bf13db60",
"fe10bea54cac4c679f2414e053b04c1e",
"f604fae45b3045c2825115d75cb3efa1",
"1145cb706e2343c796313a4d61cfd3cc",
"800dd40347e549bfb9428a4c8ddbd438",
"75177d0089eb4a4286da383f1dd13f79",
"3cf96ea420234229a847da122e59927f",
"d853e93e31704d7d92a1880f07f24846",
"9a89f9024cd34b42a27c31ef00b6a3db",
"6f0225750e2940aca0af3686a5205dc7",
"ba55a149cb124bce907cb553fa74072c",
"db0296919a874af8b880caf30068ba51",
"92f3565025464c139f6e19e1f4a7a615",
"854ff1d9a8c3443ab30204ef14ee6c31",
"e4434169065749a4ad646d8ef9b06b9e",
"56a7b0d8c9044900ad1609c460fe5724",
"c0130b58f8a341c894e36a35d1012dbd"
]
},
"id": "3pj_4Eb2kU6A",
"outputId": "9a37d29a-814d-47d5-ee1f-f2947f5dd7c5"
},
"outputs": [],
"source": [
"from huggingface_hub import HfApi\n",
"\n",
"api = HfApi()\n",
"\n",
"api.upload_file(\n",
" path_or_fileobj=\"/content/model-q4_k_m.gguf\",\n",
" path_in_repo=\"model-q4_k_m.gguf\",\n",
" repo_id=\"Jeppcode/ScalableLab2\",\n",
")\n",
"\n",
"api.upload_file(\n",
" path_or_fileobj=\"/content/model-f16.gguf\",\n",
" path_in_repo=\"model-f16.gguf\",\n",
" repo_id=\"Jeppcode/ScalableLab2\",\n",
")\n",
"\n",
"print(\"Upload complete!\")"
]
}
],
"metadata": {
"accelerator": "GPU",
"colab": {
"gpuType": "T4",
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
"015e111ca70647fb8a9cbf48ad314238": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
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