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Kajsa Lidin commited on
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1 Parent(s): c4e69bb

fix(gguf): clone llama.cpp repo and convert model to gguf with convert-hf-to-gguf.py file

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  1. train.ipynb +15 -729
train.ipynb CHANGED
@@ -15,614 +15,7 @@
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  {
@@ -652,24 +45,11 @@
652
  "print(\"CPU used:\", psutil.virtual_memory().used/1e9, \"GB\")\n"
653
  ],
654
  "metadata": {
655
- "colab": {
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- "base_uri": "https://localhost:8080/"
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  "collapsed": true,
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- "GPU allocated: 0.0 GB\n",
669
- "CPU used: 3.050508288 GB\n"
670
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  "cell_type": "code",
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@@ -706,52 +86,10 @@
706
  "notebook_login()"
707
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742
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- "VBox(children=(HTML(value='<center> <img\\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.sv…"
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768
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769
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772
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781
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782
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783
- "/usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n",
784
- "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
785
- "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
786
- "You will be able to reuse this secret in all of your notebooks.\n",
787
- "Please note that authentication is recommended but still optional to access public models or datasets.\n",
788
- " warnings.warn(\n"
789
- ]
790
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791
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792
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793
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796
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806
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807
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@@ -852,31 +159,10 @@
852
  ")"
853
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854
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855
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861
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864
- {
865
- "output_type": "error",
866
- "ename": "NotImplementedError",
867
- "evalue": "Unsloth cannot find any torch accelerator? You need a GPU.",
868
- "traceback": [
869
- "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
870
- "\u001b[0;31mNotImplementedError\u001b[0m Traceback (most recent call last)",
871
- "\u001b[0;32m/tmp/ipython-input-422719767.py\u001b[0m in \u001b[0;36m<cell line: 0>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0munsloth\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mFastLanguageModel\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;31m# max_seq_length = 2048 # Choose any! We auto support RoPE Scaling internally!\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mmax_seq_length\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m1024\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mdtype\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;31m# None for auto detection. Float16 for Tesla T4, V100, Bfloat16 for Ampere+\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
872
- "\u001b[0;32m/usr/local/lib/python3.12/dist-packages/unsloth/__init__.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 78\u001b[0m \u001b[0;31m# except:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 79\u001b[0m \u001b[0;31m# raise ImportError(\"Unsloth: Please update unsloth_zoo via `pip install --upgrade --no-cache-dir --no-deps unsloth_zoo`\")\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 80\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0munsloth_zoo\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 81\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mPackageNotFoundError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 82\u001b[0m raise ImportError(\n",
873
- "\u001b[0;32m/usr/local/lib/python3.12/dist-packages/unsloth_zoo/__init__.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 134\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 135\u001b[0m \u001b[0;31m# Get device types and other variables\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 136\u001b[0;31m from .device_type import (\n\u001b[0m\u001b[1;32m 137\u001b[0m \u001b[0mis_hip\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 138\u001b[0m \u001b[0mget_device_type\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
874
- "\u001b[0;32m/usr/local/lib/python3.12/dist-packages/unsloth_zoo/device_type.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 54\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mNotImplementedError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Unsloth currently only works on NVIDIA, AMD and Intel GPUs.\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 55\u001b[0m \u001b[0;32mpass\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 56\u001b[0;31m \u001b[0mDEVICE_TYPE\u001b[0m \u001b[0;34m:\u001b[0m \u001b[0mstr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_device_type\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 57\u001b[0m \u001b[0;31m# HIP fails for autocast and other torch functions. Use CUDA instead\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 58\u001b[0m \u001b[0mDEVICE_TYPE_TORCH\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mDEVICE_TYPE\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
875
- "\u001b[0;32m/usr/local/lib/python3.12/dist-packages/unsloth_zoo/device_type.py\u001b[0m in \u001b[0;36mget_device_type\u001b[0;34m()\u001b[0m\n\u001b[1;32m 44\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mhasattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtorch\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"accelerator\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 45\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maccelerator\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_available\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 46\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mNotImplementedError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Unsloth cannot find any torch accelerator? You need a GPU.\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 47\u001b[0m \u001b[0maccelerator\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maccelerator\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcurrent_accelerator\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 48\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0maccelerator\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m\"cuda\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"xpu\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"hip\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
876
- "\u001b[0;31mNotImplementedError\u001b[0m: Unsloth cannot find any torch accelerator? You need a GPU."
877
- ]
878
- }
879
- ]
880
  },
881
  {
882
  "cell_type": "code",
 
15
  "language_info": {
16
  "name": "python"
17
  },
18
+ "accelerator": "TPU"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
19
  },
20
  "cells": [
21
  {
 
45
  "print(\"CPU used:\", psutil.virtual_memory().used/1e9, \"GB\")\n"
46
  ],
47
  "metadata": {
 
 
 
48
  "collapsed": true,
49
+ "id": "7sw-OYaKLIb5"
 
50
  },
51
+ "execution_count": null,
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+ "outputs": []
 
 
 
 
 
 
 
 
 
53
  },
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  {
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  "cell_type": "code",
 
61
  "metadata": {
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  "id": "t3Gzr3z7LPw3"
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  },
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+ "execution_count": null,
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  "outputs": []
66
  },
67
  {
68
  "cell_type": "code",
69
+ "execution_count": null,
70
  "metadata": {
71
  "id": "TUwzrKYWu1V1"
72
  },
 
86
  "notebook_login()"
87
  ],
88
  "metadata": {
89
+ "id": "mkSDOk9Ipa3l"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
90
  },
91
+ "execution_count": null,
92
+ "outputs": []
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
93
  },
94
  {
95
  "cell_type": "code",
 
105
  ")"
106
  ],
107
  "metadata": {
108
+ "id": "59UAr7pNsS5P"
 
 
 
 
 
109
  },
110
+ "execution_count": null,
111
+ "outputs": []
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
112
  },
113
  {
114
  "cell_type": "markdown",
 
159
  ")"
160
  ],
161
  "metadata": {
162
+ "id": "QDTe7QyavVdK"
 
 
 
 
 
163
  },
164
+ "execution_count": null,
165
+ "outputs": []
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
166
  },
167
  {
168
  "cell_type": "code",