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fastnlp_in_six_lines.ipynb 1.4 kB

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  1. {
  2. "cells": [
  3. {
  4. "cell_type": "markdown",
  5. "metadata": {
  6. "collapsed": true
  7. },
  8. "source": [
  9. "# 六行代码搞定FastNLP"
  10. ]
  11. },
  12. {
  13. "cell_type": "code",
  14. "execution_count": null,
  15. "metadata": {},
  16. "outputs": [],
  17. "source": [
  18. "from fastNLP.core.dataset import DataSet\n",
  19. "import fastNLP.io.dataset_loader"
  20. ]
  21. },
  22. {
  23. "cell_type": "code",
  24. "execution_count": null,
  25. "metadata": {},
  26. "outputs": [],
  27. "source": [
  28. "ds = DataSet.read_naive(\"../test/data_for_tests/tutorial_sample_dataset.csv\")"
  29. ]
  30. },
  31. {
  32. "cell_type": "code",
  33. "execution_count": null,
  34. "metadata": {},
  35. "outputs": [],
  36. "source": []
  37. },
  38. {
  39. "cell_type": "code",
  40. "execution_count": null,
  41. "metadata": {},
  42. "outputs": [],
  43. "source": []
  44. },
  45. {
  46. "cell_type": "code",
  47. "execution_count": null,
  48. "metadata": {},
  49. "outputs": [],
  50. "source": []
  51. },
  52. {
  53. "cell_type": "code",
  54. "execution_count": null,
  55. "metadata": {},
  56. "outputs": [],
  57. "source": []
  58. }
  59. ],
  60. "metadata": {
  61. "kernelspec": {
  62. "display_name": "Python 2",
  63. "language": "python",
  64. "name": "python2"
  65. },
  66. "language_info": {
  67. "codemirror_mode": {
  68. "name": "ipython",
  69. "version": 2
  70. },
  71. "file_extension": ".py",
  72. "mimetype": "text/x-python",
  73. "name": "python",
  74. "nbconvert_exporter": "python",
  75. "pygments_lexer": "ipython2",
  76. "version": "2.7.6"
  77. }
  78. },
  79. "nbformat": 4,
  80. "nbformat_minor": 0
  81. }