Add LM in training script

.gitignore

@@ -1 +1,2 @@
-*venv
+*venv
+.ipynb_checkpoints/

eval.py

@@ -68,7 +68,7 @@ def main(args):
     dataset = load_dataset(args.dataset, args.config, split=args.split, use_auth_token=True)
 
     # for testing: only process the first two examples as a test
-    dataset = dataset.select(range(10))
+    # dataset = dataset.select(range(10))
 
     # load processor
     feature_extractor = AutoFeatureExtractor.from_pretrained(args.model_id)

requirements.txt

@@ -3,3 +3,5 @@ torch >= 1.5
 torchaudio
 librosa
 jiwer
+wandb
+pyctcdecode

run.sh

@@ -31,4 +31,5 @@ python run_speech_recognition_ctc.py \
 	--fp16 \
 	--group_by_length \
 	--do_train --do_eval \
-	--push_to_hub
+	--push_to_hub \
+	--push_lm_to_hub

run_speech_recognition_ctc.py

@@ -31,6 +31,7 @@ import numpy as np
 import torch
 import wandb
 from datasets import DatasetDict, load_dataset, load_metric
+from pyctcdecode import build_ctcdecoder
 
 import transformers
 from transformers import (
@@ -43,6 +44,7 @@ from transformers import (
     Trainer,
     TrainingArguments,
     Wav2Vec2Processor,
+    Wav2Vec2ProcessorWithLM,
     set_seed,
 )
 from transformers.trainer_utils import get_last_checkpoint, is_main_process
@@ -359,7 +361,8 @@ def main():
 
     # TODO: Replace with check of wandb env vars
     try:
-        os.environ["WANDB_PROJECT"] = os.getcwd().split("/")[-1]
+        repo_name = os.getcwd().split("/")[-1]
+        os.environ["WANDB_PROJECT"] = repo_name
         wandb.login()
         training_args.report_to = ["wandb"]
         training_args.run_name = f"{datetime.datetime.utcnow()}".replace(" ", "T")
@@ -740,6 +743,23 @@ def main():
         trainer.push_to_hub(**kwargs)
     else:
         trainer.create_model_card(**kwargs)
+    
+    if training_args.push_lm_to_hub:
+        vocab_dict = processor.tokenizer.get_vocab()
+        sorted_vocab_dict = {k.lower(): v for k, v in sorted(vocab_dict.items(), key=lambda item: item[1])}
+
+        decoder = build_ctcdecoder(
+            labels=list(sorted_vocab_dict.keys()),
+            kenlm_model_path="5gram_sv_lm.bin",
+        )
+
+        processor_with_lm = Wav2Vec2ProcessorWithLM(
+            feature_extractor=processor.feature_extractor,
+            tokenizer=processor.tokenizer,
+            decoder=decoder
+        )
+        processor_with_lm.save_pretrained(repo_name)
+        processor_with_lm.push_to_hub(**kwargs)
 
     return results
 

train_n_gram_lm_with_KenLM.ipynb

@@ -0,0 +1,2262 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Train n-gram language model with KenLM on Colab"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "PtkgQE7--Ufg"
+   },
+   "source": [
+    "See https://colab.research.google.com/github/patrickvonplaten/notebooks/blob/master/Boosting_Wav2Vec2_with_n_grams_in_Transformers.ipynb#scrollTo=X9qg4FPt2zi8 for detailed explanation on how to use KenLM to boost wav2vec2 fine-tuned models on 🤗"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "VBCqCboC6Soc"
+   },
+   "source": [
+    "Install KenLM"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "-CKLr9bI6GPE",
+    "outputId": "0c6d917e-4896-4e35-c92f-4b085f77c893"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The operation couldn’t be completed. Unable to locate a Java Runtime that supports apt.\r\n",
+      "Please visit http://www.java.com for information on installing Java.\r\n",
+      "\r\n"
+     ]
+    }
+   ],
+   "source": [
+    "!sudo apt install build-essential cmake libboost-system-dev libboost-thread-dev libboost-program-options-dev libboost-test-dev libeigen3-dev zlib1g-dev libbz2-dev liblzma-dev"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "TIlrFi3M6XO4",
+    "outputId": "7c986a6f-f84c-4d29-b3f8-941cb85e6e8d"
+   },
+   "outputs": [],
+   "source": [
+    "!wget -O - https://kheafield.com/code/kenlm.tar.gz | tar xz"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "KGwSg6Bl6a8Y",
+    "outputId": "025562ab-679d-4986-9474-334dc8bd834e"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "-- The C compiler identification is GNU 7.5.0\n",
+      "-- The CXX compiler identification is GNU 7.5.0\n",
+      "-- Check for working C compiler: /usr/bin/cc\n",
+      "-- Check for working C compiler: /usr/bin/cc -- works\n",
+      "-- Detecting C compiler ABI info\n",
+      "-- Detecting C compiler ABI info - done\n",
+      "-- Detecting C compile features\n",
+      "-- Detecting C compile features - done\n",
+      "-- Check for working CXX compiler: /usr/bin/c++\n",
+      "-- Check for working CXX compiler: /usr/bin/c++ -- works\n",
+      "-- Detecting CXX compiler ABI info\n",
+      "-- Detecting CXX compiler ABI info - done\n",
+      "-- Detecting CXX compile features\n",
+      "-- Detecting CXX compile features - done\n",
+      "-- Looking for pthread.h\n",
+      "-- Looking for pthread.h - found\n",
+      "-- Looking for pthread_create\n",
+      "-- Looking for pthread_create - not found\n",
+      "-- Looking for pthread_create in pthreads\n",
+      "-- Looking for pthread_create in pthreads - not found\n",
+      "-- Looking for pthread_create in pthread\n",
+      "-- Looking for pthread_create in pthread - found\n",
+      "-- Found Threads: TRUE  \n",
+      "-- Boost version: 1.65.1\n",
+      "-- Found the following Boost libraries:\n",
+      "--   program_options\n",
+      "--   system\n",
+      "--   thread\n",
+      "--   unit_test_framework\n",
+      "--   chrono\n",
+      "--   date_time\n",
+      "--   atomic\n",
+      "-- Check if compiler accepts -pthread\n",
+      "-- Check if compiler accepts -pthread - yes\n",
+      "-- Found ZLIB: /usr/lib/x86_64-linux-gnu/libz.so (found version \"1.2.11\") \n",
+      "-- Found BZip2: /usr/lib/x86_64-linux-gnu/libbz2.so (found version \"1.0.6\") \n",
+      "-- Looking for BZ2_bzCompressInit\n",
+      "-- Looking for BZ2_bzCompressInit - found\n",
+      "-- Looking for lzma_auto_decoder in /usr/lib/x86_64-linux-gnu/liblzma.so\n",
+      "-- Looking for lzma_auto_decoder in /usr/lib/x86_64-linux-gnu/liblzma.so - found\n",
+      "-- Looking for lzma_easy_encoder in /usr/lib/x86_64-linux-gnu/liblzma.so\n",
+      "-- Looking for lzma_easy_encoder in /usr/lib/x86_64-linux-gnu/liblzma.so - found\n",
+      "-- Looking for lzma_lzma_preset in /usr/lib/x86_64-linux-gnu/liblzma.so\n",
+      "-- Looking for lzma_lzma_preset in /usr/lib/x86_64-linux-gnu/liblzma.so - found\n",
+      "-- Found LibLZMA: /usr/include (found version \"5.2.2\") \n",
+      "-- Found OpenMP_C: -fopenmp (found version \"4.5\") \n",
+      "-- Found OpenMP_CXX: -fopenmp (found version \"4.5\") \n",
+      "-- Found OpenMP: TRUE (found version \"4.5\")  \n",
+      "-- Configuring done\n",
+      "-- Generating done\n",
+      "-- Build files have been written to: /content/kenlm/build\n",
+      "\u001b[35m\u001b[1mScanning dependencies of target kenlm_util\u001b[0m\n",
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+      "[ 27%] \u001b[32mBuilding CXX object util/CMakeFiles/kenlm_util.dir/read_compressed.cc.o\u001b[0m\n",
+      "[ 28%] \u001b[32mBuilding CXX object util/CMakeFiles/kenlm_util.dir/scoped.cc.o\u001b[0m\n",
+      "[ 29%] \u001b[32mBuilding CXX object util/CMakeFiles/kenlm_util.dir/spaces.cc.o\u001b[0m\n",
+      "[ 30%] \u001b[32mBuilding CXX object util/CMakeFiles/kenlm_util.dir/string_piece.cc.o\u001b[0m\n",
+      "[ 31%] \u001b[32mBuilding CXX object util/CMakeFiles/kenlm_util.dir/usage.cc.o\u001b[0m\n",
+      "[ 32%] \u001b[32m\u001b[1mLinking CXX static library ../lib/libkenlm_util.a\u001b[0m\n",
+      "[ 32%] Built target kenlm_util\n",
+      "\u001b[35m\u001b[1mScanning dependencies of target probing_hash_table_benchmark\u001b[0m\n",
+      "\u001b[35m\u001b[1mScanning dependencies of target kenlm\u001b[0m\n",
+      "[ 33%] \u001b[32mBuilding CXX object util/CMakeFiles/probing_hash_table_benchmark.dir/probing_hash_table_benchmark_main.cc.o\u001b[0m\n",
+      "[ 34%] \u001b[32mBuilding CXX object lm/CMakeFiles/kenlm.dir/bhiksha.cc.o\u001b[0m\n",
+      "[ 35%] \u001b[32mBuilding CXX object lm/CMakeFiles/kenlm.dir/binary_format.cc.o\u001b[0m\n",
+      "[ 36%] \u001b[32mBuilding CXX object lm/CMakeFiles/kenlm.dir/config.cc.o\u001b[0m\n",
+      "[ 37%] \u001b[32mBuilding CXX object lm/CMakeFiles/kenlm.dir/lm_exception.cc.o\u001b[0m\n",
+      "[ 38%] \u001b[32mBuilding CXX object lm/CMakeFiles/kenlm.dir/model.cc.o\u001b[0m\n",
+      "[ 39%] \u001b[32mBuilding CXX object lm/CMakeFiles/kenlm.dir/quantize.cc.o\u001b[0m\n",
+      "[ 40%] \u001b[32mBuilding CXX object lm/CMakeFiles/kenlm.dir/read_arpa.cc.o\u001b[0m\n",
+      "[ 41%] \u001b[32m\u001b[1mLinking CXX executable ../bin/probing_hash_table_benchmark\u001b[0m\n",
+      "[ 41%] Built target probing_hash_table_benchmark\n",
+      "\u001b[35m\u001b[1mScanning dependencies of target kenlm_filter\u001b[0m\n",
+      "[ 42%] \u001b[32mBuilding CXX object lm/filter/CMakeFiles/kenlm_filter.dir/arpa_io.cc.o\u001b[0m\n",
+      "[ 43%] \u001b[32mBuilding CXX object lm/CMakeFiles/kenlm.dir/search_hashed.cc.o\u001b[0m\n",
+      "[ 44%] \u001b[32mBuilding CXX object lm/filter/CMakeFiles/kenlm_filter.dir/phrase.cc.o\u001b[0m\n",
+      "[ 45%] \u001b[32mBuilding CXX object lm/CMakeFiles/kenlm.dir/search_trie.cc.o\u001b[0m\n",
+      "[ 46%] \u001b[32mBuilding CXX object lm/filter/CMakeFiles/kenlm_filter.dir/vocab.cc.o\u001b[0m\n",
+      "[ 47%] \u001b[32m\u001b[1mLinking CXX static library ../../lib/libkenlm_filter.a\u001b[0m\n",
+      "[ 47%] Built target kenlm_filter\n",
+      "[ 48%] \u001b[32mBuilding CXX object lm/CMakeFiles/kenlm.dir/sizes.cc.o\u001b[0m\n",
+      "[ 50%] \u001b[32mBuilding CXX object lm/CMakeFiles/kenlm.dir/trie.cc.o\u001b[0m\n",
+      "[ 51%] \u001b[32mBuilding CXX object lm/CMakeFiles/kenlm.dir/trie_sort.cc.o\u001b[0m\n",
+      "[ 52%] \u001b[32mBuilding CXX object lm/CMakeFiles/kenlm.dir/value_build.cc.o\u001b[0m\n",
+      "[ 53%] \u001b[32mBuilding CXX object lm/CMakeFiles/kenlm.dir/virtual_interface.cc.o\u001b[0m\n",
+      "[ 54%] \u001b[32mBuilding CXX object lm/CMakeFiles/kenlm.dir/vocab.cc.o\u001b[0m\n",
+      "[ 55%] \u001b[32mBuilding CXX object lm/CMakeFiles/kenlm.dir/common/model_buffer.cc.o\u001b[0m\n",
+      "[ 56%] \u001b[32mBuilding CXX object lm/CMakeFiles/kenlm.dir/common/print.cc.o\u001b[0m\n",
+      "[ 57%] \u001b[32mBuilding CXX object lm/CMakeFiles/kenlm.dir/common/renumber.cc.o\u001b[0m\n",
+      "[ 58%] \u001b[32mBuilding CXX object lm/CMakeFiles/kenlm.dir/common/size_option.cc.o\u001b[0m\n",
+      "[ 59%] \u001b[32m\u001b[1mLinking CXX static library ../lib/libkenlm.a\u001b[0m\n",
+      "[ 59%] Built target kenlm\n",
+      "\u001b[35m\u001b[1mScanning dependencies of target build_binary\u001b[0m\n",
+      "\u001b[35m\u001b[1mScanning dependencies of target fragment\u001b[0m\n",
+      "[ 60%] \u001b[32mBuilding CXX object lm/CMakeFiles/fragment.dir/fragment_main.cc.o\u001b[0m\n",
+      "[ 61%] \u001b[32mBuilding CXX object lm/CMakeFiles/build_binary.dir/build_binary_main.cc.o\u001b[0m\n",
+      "[ 62%] \u001b[32m\u001b[1mLinking CXX executable ../bin/fragment\u001b[0m\n",
+      "[ 63%] \u001b[32m\u001b[1mLinking CXX executable ../bin/build_binary\u001b[0m\n",
+      "[ 63%] Built target fragment\n",
+      "\u001b[35m\u001b[1mScanning dependencies of target kenlm_benchmark\u001b[0m\n",
+      "[ 64%] \u001b[32mBuilding CXX object lm/CMakeFiles/kenlm_benchmark.dir/kenlm_benchmark_main.cc.o\u001b[0m\n",
+      "[ 64%] Built target build_binary\n",
+      "\u001b[35m\u001b[1mScanning dependencies of target query\u001b[0m\n",
+      "[ 65%] \u001b[32mBuilding CXX object lm/CMakeFiles/query.dir/query_main.cc.o\u001b[0m\n",
+      "[ 66%] \u001b[32m\u001b[1mLinking CXX executable ../bin/query\u001b[0m\n",
+      "[ 66%] Built target query\n",
+      "\u001b[35m\u001b[1mScanning dependencies of target kenlm_builder\u001b[0m\n",
+      "[ 67%] \u001b[32mBuilding CXX object lm/builder/CMakeFiles/kenlm_builder.dir/adjust_counts.cc.o\u001b[0m\n",
+      "[ 68%] \u001b[32mBuilding CXX object lm/builder/CMakeFiles/kenlm_builder.dir/corpus_count.cc.o\u001b[0m\n",
+      "[ 69%] \u001b[32mBuilding CXX object lm/builder/CMakeFiles/kenlm_builder.dir/initial_probabilities.cc.o\u001b[0m\n",
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+      "[ 72%] \u001b[32mBuilding CXX object lm/builder/CMakeFiles/kenlm_builder.dir/output.cc.o\u001b[0m\n",
+      "[ 72%] Built target kenlm_benchmark\n",
+      "\u001b[35m\u001b[1mScanning dependencies of target phrase_table_vocab\u001b[0m\n",
+      "[ 73%] \u001b[32mBuilding CXX object lm/filter/CMakeFiles/phrase_table_vocab.dir/phrase_table_vocab_main.cc.o\u001b[0m\n",
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+      "[ 75%] Built target phrase_table_vocab\n",
+      "\u001b[35m\u001b[1mScanning dependencies of target filter\u001b[0m\n",
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+      "[ 78%] Built target kenlm_builder\n",
+      "\u001b[35m\u001b[1mScanning dependencies of target kenlm_interpolate\u001b[0m\n",
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+      "[ 90%] \u001b[32mBuilding CXX object lm/interpolate/CMakeFiles/kenlm_interpolate.dir/split_worker.cc.o\u001b[0m\n",
+      "[ 91%] \u001b[32mBuilding CXX object lm/interpolate/CMakeFiles/kenlm_interpolate.dir/tune_derivatives.cc.o\u001b[0m\n",
+      "[ 92%] \u001b[32mBuilding CXX object lm/interpolate/CMakeFiles/kenlm_interpolate.dir/tune_instances.cc.o\u001b[0m\n",
+      "[ 93%] \u001b[32mBuilding CXX object lm/interpolate/CMakeFiles/kenlm_interpolate.dir/tune_weights.cc.o\u001b[0m\n",
+      "[ 94%] \u001b[32mBuilding CXX object lm/interpolate/CMakeFiles/kenlm_interpolate.dir/universal_vocab.cc.o\u001b[0m\n",
+      "[ 95%] \u001b[32m\u001b[1mLinking CXX static library ../../lib/libkenlm_interpolate.a\u001b[0m\n",
+      "[ 95%] Built target kenlm_interpolate\n",
+      "\u001b[35m\u001b[1mScanning dependencies of target streaming_example\u001b[0m\n",
+      "\u001b[35m\u001b[1mScanning dependencies of target interpolate\u001b[0m\n",
+      "[ 96%] \u001b[32mBuilding CXX object lm/interpolate/CMakeFiles/streaming_example.dir/streaming_example_main.cc.o\u001b[0m\n",
+      "[ 97%] \u001b[32mBuilding CXX object lm/interpolate/CMakeFiles/interpolate.dir/interpolate_main.cc.o\u001b[0m\n",
+      "[ 98%] \u001b[32m\u001b[1mLinking CXX executable ../../bin/interpolate\u001b[0m\n",
+      "[ 98%] Built target interpolate\n",
+      "[100%] \u001b[32m\u001b[1mLinking CXX executable ../../bin/streaming_example\u001b[0m\n",
+      "[100%] Built target streaming_example\n",
+      "build_binary  fragment\t       lmplz\t\t\t     query\n",
+      "count_ngrams  interpolate      phrase_table_vocab\t     streaming_example\n",
+      "filter\t      kenlm_benchmark  probing_hash_table_benchmark\n"
+     ]
+    }
+   ],
+   "source": [
+    "!mkdir kenlm/build && cd kenlm/build && cmake .. && make -j2\n",
+    "!ls kenlm/build/bin"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "rUUGXbDy6x7r"
+   },
+   "source": [
+    "Install 🤗 dependencies"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "Gs8LAZKr6wF8",
+    "outputId": "2a1785bb-f254-487a-ef4c-e496f037145a"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting datasets\n",
+      "  Downloading datasets-1.18.0-py3-none-any.whl (311 kB)\n",
+      "\u001b[K     |████████████████████████████████| 311 kB 5.3 MB/s \n",
+      "\u001b[?25hCollecting transformers\n",
+      "  Downloading transformers-4.15.0-py3-none-any.whl (3.4 MB)\n",
+      "\u001b[K     |████████████████████████████████| 3.4 MB 39.8 MB/s \n",
+      "\u001b[?25hRequirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.7/dist-packages (from datasets) (2.23.0)\n",
+      "Collecting aiohttp\n",
+      "  Downloading aiohttp-3.8.1-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.1 MB)\n",
+      "\u001b[K     |████████████████████████████████| 1.1 MB 54.7 MB/s \n",
+      "\u001b[?25hRequirement already satisfied: pyarrow!=4.0.0,>=3.0.0 in /usr/local/lib/python3.7/dist-packages (from datasets) (3.0.0)\n",
+      "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.7/dist-packages (from datasets) (1.19.5)\n",
+      "Collecting xxhash\n",
+      "  Downloading xxhash-2.0.2-cp37-cp37m-manylinux2010_x86_64.whl (243 kB)\n",
+      "\u001b[K     |████████████████████████████████| 243 kB 41.5 MB/s \n",
+      "\u001b[?25hRequirement already satisfied: dill in /usr/local/lib/python3.7/dist-packages (from datasets) (0.3.4)\n",
+      "Requirement already satisfied: tqdm>=4.62.1 in /usr/local/lib/python3.7/dist-packages (from datasets) (4.62.3)\n",
+      "Collecting huggingface-hub<1.0.0,>=0.1.0\n",
+      "  Downloading huggingface_hub-0.4.0-py3-none-any.whl (67 kB)\n",
+      "\u001b[K     |████████████████████████████████| 67 kB 5.1 MB/s \n",
+      "\u001b[?25hRequirement already satisfied: packaging in /usr/local/lib/python3.7/dist-packages (from datasets) (21.3)\n",
+      "Collecting fsspec[http]>=2021.05.0\n",
+      "  Downloading fsspec-2022.1.0-py3-none-any.whl (133 kB)\n",
+      "\u001b[K     |████████████████████████████████| 133 kB 50.2 MB/s \n",
+      "\u001b[?25hRequirement already satisfied: multiprocess in /usr/local/lib/python3.7/dist-packages (from datasets) (0.70.12.2)\n",
+      "Requirement already satisfied: importlib-metadata in /usr/local/lib/python3.7/dist-packages (from datasets) (4.10.0)\n",
+      "Requirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (from datasets) (1.1.5)\n",
+      "Requirement already satisfied: filelock in /usr/local/lib/python3.7/dist-packages (from huggingface-hub<1.0.0,>=0.1.0->datasets) (3.4.2)\n",
+      "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.7/dist-packages (from huggingface-hub<1.0.0,>=0.1.0->datasets) (3.10.0.2)\n",
+      "Requirement already satisfied: pyyaml in /usr/local/lib/python3.7/dist-packages (from huggingface-hub<1.0.0,>=0.1.0->datasets) (3.13)\n",
+      "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from packaging->datasets) (3.0.6)\n",
+      "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->datasets) (3.0.4)\n",
+      "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->datasets) (1.24.3)\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->datasets) (2021.10.8)\n",
+      "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->datasets) (2.10)\n",
+      "Collecting pyyaml\n",
+      "  Downloading PyYAML-6.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (596 kB)\n",
+      "\u001b[K     |████████████████████████████████| 596 kB 56.2 MB/s \n",
+      "\u001b[?25hCollecting tokenizers<0.11,>=0.10.1\n",
+      "  Downloading tokenizers-0.10.3-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (3.3 MB)\n",
+      "\u001b[K     |████████████████████████████████| 3.3 MB 46.1 MB/s \n",
+      "\u001b[?25hCollecting sacremoses\n",
+      "  Downloading sacremoses-0.0.47-py2.py3-none-any.whl (895 kB)\n",
+      "\u001b[K     |████████████████████████████████| 895 kB 51.6 MB/s \n",
+      "\u001b[?25hRequirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.7/dist-packages (from transformers) (2019.12.20)\n",
+      "Collecting frozenlist>=1.1.1\n",
+      "  Downloading frozenlist-1.3.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (144 kB)\n",
+      "\u001b[K     |████████████████████████████████| 144 kB 51.5 MB/s \n",
+      "\u001b[?25hCollecting yarl<2.0,>=1.0\n",
+      "  Downloading yarl-1.7.2-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (271 kB)\n",
+      "\u001b[K     |████████████████████████████████| 271 kB 56.7 MB/s \n",
+      "\u001b[?25hCollecting asynctest==0.13.0\n",
+      "  Downloading asynctest-0.13.0-py3-none-any.whl (26 kB)\n",
+      "Requirement already satisfied: charset-normalizer<3.0,>=2.0 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets) (2.0.10)\n",
+      "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets) (21.4.0)\n",
+      "Collecting multidict<7.0,>=4.5\n",
+      "  Downloading multidict-6.0.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (94 kB)\n",
+      "\u001b[K     |████████████████████████████████| 94 kB 3.0 MB/s \n",
+      "\u001b[?25hCollecting aiosignal>=1.1.2\n",
+      "  Downloading aiosignal-1.2.0-py3-none-any.whl (8.2 kB)\n",
+      "Collecting async-timeout<5.0,>=4.0.0a3\n",
+      "  Downloading async_timeout-4.0.2-py3-none-any.whl (5.8 kB)\n",
+      "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata->datasets) (3.7.0)\n",
+      "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.7/dist-packages (from pandas->datasets) (2018.9)\n",
+      "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas->datasets) (2.8.2)\n",
+      "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas->datasets) (1.15.0)\n",
+      "Requirement already satisfied: click in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers) (7.1.2)\n",
+      "Requirement already satisfied: joblib in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers) (1.1.0)\n",
+      "Installing collected packages: multidict, frozenlist, yarl, asynctest, async-timeout, aiosignal, pyyaml, fsspec, aiohttp, xxhash, tokenizers, sacremoses, huggingface-hub, transformers, datasets\n",
+      "  Attempting uninstall: pyyaml\n",
+      "    Found existing installation: PyYAML 3.13\n",
+      "    Uninstalling PyYAML-3.13:\n",
+      "      Successfully uninstalled PyYAML-3.13\n",
+      "Successfully installed aiohttp-3.8.1 aiosignal-1.2.0 async-timeout-4.0.2 asynctest-0.13.0 datasets-1.18.0 frozenlist-1.3.0 fsspec-2022.1.0 huggingface-hub-0.4.0 multidict-6.0.2 pyyaml-6.0 sacremoses-0.0.47 tokenizers-0.10.3 transformers-4.15.0 xxhash-2.0.2 yarl-1.7.2\n"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install datasets transformers"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "6RoHBmOz66fz"
+   },
+   "source": [
+    "Load preprocessed dataset from 🤗 and write it to file as required by KenLM"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 216,
+     "referenced_widgets": [
+      "ad5d7b0bc9ad4e228b3bc76bc975cc47",
+      "5925567ffea2436691c4ed3b7b147c17",
+      "799acae3451445f0a3616b8932f2e3f3",
+      "1714ea91694842339756f26b2fa9c725",
+      "b5d6b069468246abbb3207f3df6f9dde",
+      "5a9c9d4b60e54a3bb64c576707bd9736",
+      "789d5845a82e48fe9c629af743b5b1f0",
+      "e3414cc0456241eca109f4e9e115d16a",
+      "d3e6acd54d024d6791aab76232557721",
+      "6b43ea2d93c04965a4539b3ef839893b",
+      "4958b4c72d0c48af9a77974fc4ed449c",
+      "d722bbfffeaf4ea7a1060d10dc3a06db",
+      "e81b0bf92adc4aadaafce4ee7d36421e",
+      "a4b5b93b88f549e8a4f37f3d48834ca9",
+      "82692c41501c487fad27c6b19836f46f",
+      "af8f433ef2f540c9bd70d14421904d83",
+      "5e469744bf6a4813983ae8ee727c1c5e",
+      "34c5f87238cb4f13a03b207aa7dc1d18",
+      "c7955974289a4f448b422d7e4640131a",
+      "db7ee45589e04749b80376e25ee377bb",
+      "34d9460b112c419885bbff5211674cb3",
+      "033cb43d32314d279a7b9e1e86bbccdc",
+      "6a7e3547dc4141e7b5937f2baff58cbf",
+      "921a3c1f50a24979838fd560c2cea9e0",
+      "e33033ecda374ed4966ae5fccf6efe37",
+      "52a852c0f98c49aa9e5edfdd4f91e4ca",
+      "d1ff84cb5591449abcc7dd3e37f9a2df",
+      "f479a9629c414cb495a97b0741b0fe4b",
+      "a41cf7f5121a4068842bb5c7d2bc4d62",
+      "31b2d7d8d9054c8fb47bf1b58043aee1",
+      "23c9da8dd7bf4be9a23357806ebfc036",
+      "e084d47529ca4131b233ea3514a6344f",
+      "a6e3c5ce0a3c49ffb3d7cbf92568fe47",
+      "a1eca879a11f414f8173b0c2c260f4c3",
+      "75130a60f93b49c8bee0986665121d02",
+      "328cea1a2aac4fb58bceeaf126b99371",
+      "662d61fdd89d434785e74a7038427fbc",
+      "670d4f16a7e44144afc0ac70eea59325",
+      "7f92331b29fd49a68815b6d7389c1005",
+      "c710ba94fd65486cbcbe1d402919e27f",
+      "5951d1bafdd548b6b835b28cf9960533",
+      "adcffda7f78c4a1c8bdc6010c8704292",
+      "2c37aaee1f524837b477dc584209733a",
+      "0bee4735e017471fa8679ad984b88633"
+     ]
+    },
+    "id": "0bDpNg9c6mUu",
+    "outputId": "677d294f-2e37-48d5-bab0-6e21d1b4fe30"
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "ad5d7b0bc9ad4e228b3bc76bc975cc47",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading:   0%|          | 0.00/1.16k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Using custom data configuration hf-test--swedish_corpora_parliament_processed-56ded20e2faa0852\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading and preparing dataset europarl_bilingual/en-sv (download: 151.40 MiB, generated: 278.82 MiB, post-processed: Unknown size, total: 430.21 MiB) to /root/.cache/huggingface/datasets/parquet/hf-test--swedish_corpora_parliament_processed-56ded20e2faa0852/0.0.0/1638526fd0e8d960534e2155dc54fdff8dce73851f21f031d2fb9c2cf757c121...\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "d722bbfffeaf4ea7a1060d10dc3a06db",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/1 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6a7e3547dc4141e7b5937f2baff58cbf",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading:   0%|          | 0.00/159M [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a1eca879a11f414f8173b0c2c260f4c3",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/1 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Dataset parquet downloaded and prepared to /root/.cache/huggingface/datasets/parquet/hf-test--swedish_corpora_parliament_processed-56ded20e2faa0852/0.0.0/1638526fd0e8d960534e2155dc54fdff8dce73851f21f031d2fb9c2cf757c121. Subsequent calls will reuse this data.\n"
+     ]
+    }
+   ],
+   "source": [
+    "from datasets import load_dataset\n",
+    "\n",
+    "# change to your dataset path\n",
+    "username = \"hf-test\"  \n",
+    "target_lang = \"sv\"\n",
+    "\n",
+    "dataset = load_dataset(f\"{username}/{target_lang}_corpora_parliament_processed\", split=\"train\")\n",
+    "\n",
+    "with open(\"text.txt\", \"w\") as file:\n",
+    "  file.write(\" \".join(dataset[\"text\"]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "z8PqeGC17jD8"
+   },
+   "source": [
+    "Train 5-gram language model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "_8KoINuj7h-1",
+    "outputId": "26e0622d-6cb6-4329-e722-91ae9df263c7"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "=== 1/5 Counting and sorting n-grams ===\n",
+      "Reading /content/text.txt\n",
+      "----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100\n",
+      "tcmalloc: large alloc 1918697472 bytes == 0x5623caa4e000 @  0x7fe627aa41e7 0x5623c8d517a2 0x5623c8cec51e 0x5623c8ccb2eb 0x5623c8cb7066 0x7fe625c3dbf7 0x5623c8cb8baa\n",
+      "tcmalloc: large alloc 8953896960 bytes == 0x56243d01e000 @  0x7fe627aa41e7 0x5623c8d517a2 0x5623c8d407ca 0x5623c8d41208 0x5623c8ccb308 0x5623c8cb7066 0x7fe625c3dbf7 0x5623c8cb8baa\n",
+      "****************************************************************************************************\n",
+      "Unigram tokens 42153890 types 360209\n",
+      "=== 2/5 Calculating and sorting adjusted counts ===\n",
+      "Chain sizes: 1:4322508 2:1062773568 3:1992700672 4:3188320768 5:4649634816\n",
+      "tcmalloc: large alloc 4649639936 bytes == 0x5623caa4e000 @  0x7fe627aa41e7 0x5623c8d517a2 0x5623c8d407ca 0x5623c8d41208 0x5623c8ccb8d7 0x5623c8cb7066 0x7fe625c3dbf7 0x5623c8cb8baa\n",
+      "tcmalloc: large alloc 1992704000 bytes == 0x56251f640000 @  0x7fe627aa41e7 0x5623c8d517a2 0x5623c8d407ca 0x5623c8d41208 0x5623c8ccbcdd 0x5623c8cb7066 0x7fe625c3dbf7 0x5623c8cb8baa\n",
+      "tcmalloc: large alloc 3188326400 bytes == 0x5626533e4000 @  0x7fe627aa41e7 0x5623c8d517a2 0x5623c8d407ca 0x5623c8d41208 0x5623c8ccbcdd 0x5623c8cb7066 0x7fe625c3dbf7 0x5623c8cb8baa\n",
+      "Statistics:\n",
+      "1 360208 D1=0.686222 D2=1.01595 D3+=1.33685\n",
+      "2 5476741 D1=0.761523 D2=1.06735 D3+=1.32559\n",
+      "3 18177681 D1=0.839918 D2=1.12061 D3+=1.33794\n",
+      "4 30374983 D1=0.909146 D2=1.20496 D3+=1.37235\n",
+      "5 37231651 D1=0.944104 D2=1.25164 D3+=1.344\n",
+      "Memory estimate for binary LM:\n",
+      "type      MB\n",
+      "probing 1884 assuming -p 1.5\n",
+      "probing 2195 assuming -r models -p 1.5\n",
+      "trie     922 without quantization\n",
+      "trie     518 assuming -q 8 -b 8 quantization \n",
+      "trie     806 assuming -a 22 array pointer compression\n",
+      "trie     401 assuming -a 22 -q 8 -b 8 array pointer compression and quantization\n",
+      "=== 3/5 Calculating and sorting initial probabilities ===\n",
+      "Chain sizes: 1:4322496 2:87627856 3:363553620 4:728999592 5:1042486228\n",
+      "----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100\n",
+      "####################################################################################################\n",
+      "=== 4/5 Calculating and writing order-interpolated probabilities ===\n",
+      "Chain sizes: 1:4322496 2:87627856 3:363553620 4:728999592 5:1042486228\n",
+      "----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100\n",
+      "####################################################################################################\n",
+      "=== 5/5 Writing ARPA model ===\n",
+      "----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100\n",
+      "****************************************************************************************************\n",
+      "Name:lmplz\tVmPeak:14181536 kB\tVmRSS:2199072 kB\tRSSMax:4117540 kB\tuser:125.411\tsys:25.1745\tCPU:150.586\treal:290.479\n"
+     ]
+    }
+   ],
+   "source": [
+    "!kenlm/build/bin/lmplz -o 5 <\"text.txt\" > \"5gram.arpa\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "ZJ5OKh358nwR"
+   },
+   "source": [
+    "Check head of file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "pv93ZCR68s4m",
+    "outputId": "9489b8a8-789d-4779-85f4-f4aa4e0b3392"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\\data\\\n",
+      "ngram 1=360208\n",
+      "ngram 2=5476741\n",
+      "ngram 3=18177681\n",
+      "ngram 4=30374983\n",
+      "ngram 5=37231651\n",
+      "\n",
+      "\\1-grams:\n",
+      "-6.770219\t<unk>\t0\n",
+      "0\t<s>\t-0.11831701\n",
+      "-4.6095004\tåterupptagande\t-1.2174699\n",
+      "-2.2361007\tav\t-0.79668784\n",
+      "-4.8163533\tsessionen\t-0.37327805\n",
+      "-2.2251768\tjag\t-1.4205662\n",
+      "-4.181505\tförklarar\t-0.56261665\n",
+      "-3.5790775\teuropaparlamentets\t-0.63611007\n",
+      "-4.771945\tsession\t-0.3647111\n",
+      "-5.8043895\tåterupptagen\t-0.3058712\n",
+      "-2.8580177\tefter\t-0.7557702\n",
+      "-5.199537\tavbrottet\t-0.43322718\n"
+     ]
+    }
+   ],
+   "source": [
+    "!head -20 5gram.arpa"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "FEcPijF77mPY"
+   },
+   "source": [
+    "Add end-of-sentence token \"\\</s>\" "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "id": "Sktd-U5a7yZL"
+   },
+   "outputs": [],
+   "source": [
+    "with open(\"5gram.arpa\", \"r\") as read_file, open(\"5gram_sv_lm.arpa\", \"w\") as write_file:\n",
+    "  has_added_eos = False\n",
+    "  for line in read_file:\n",
+    "    if not has_added_eos and \"ngram 1=\" in line:\n",
+    "      count=line.strip().split(\"=\")[-1]\n",
+    "      write_file.write(line.replace(f\"{count}\", f\"{int(count)+1}\"))\n",
+    "    elif not has_added_eos and \"<s>\" in line:\n",
+    "      write_file.write(line)\n",
+    "      write_file.write(line.replace(\"<s>\", \"</s>\"))\n",
+    "      has_added_eos = True\n",
+    "    else:\n",
+    "      write_file.write(line)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "hqXHYY-K760Q"
+   },
+   "source": [
+    "Check head of file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "0QuHk3AY8Hax",
+    "outputId": "090d065f-95c7-48e5-bc0c-01069f69c619"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\\data\\\n",
+      "ngram 1=360209\n",
+      "ngram 2=5476741\n",
+      "ngram 3=18177681\n",
+      "ngram 4=30374983\n",
+      "ngram 5=37231651\n",
+      "\n",
+      "\\1-grams:\n",
+      "-6.770219\t<unk>\t0\n",
+      "0\t<s>\t-0.11831701\n",
+      "0\t</s>\t-0.11831701\n",
+      "-4.6095004\tåterupptagande\t-1.2174699\n",
+      "-2.2361007\tav\t-0.79668784\n",
+      "-4.8163533\tsessionen\t-0.37327805\n",
+      "-2.2251768\tjag\t-1.4205662\n",
+      "-4.181505\tförklarar\t-0.56261665\n",
+      "-3.5790775\teuropaparlamentets\t-0.63611007\n",
+      "-4.771945\tsession\t-0.3647111\n",
+      "-5.8043895\tåterupptagen\t-0.3058712\n",
+      "-2.8580177\tefter\t-0.7557702\n"
+     ]
+    }
+   ],
+   "source": [
+    "!head -20 5gram_sv_lm.arpa"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "kTvRntrZ9-uq"
+   },
+   "source": [
+    "Compress arpa file by converting it to bin"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "DnmOlNZ5-ClT",
+    "outputId": "c380c05a-e335-4e9d-98b2-c015645a2d40"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Reading 5gram_sv_lm.arpa\n",
+      "----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100\n",
+      "****************************************************************************************************\n",
+      "SUCCESS\n"
+     ]
+    }
+   ],
+   "source": [
+    "!kenlm/build/bin/build_binary 5gram_sv_lm.arpa 5gram_sv_lm.bin"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Xra-pM-M8MZj"
+   },
+   "source": [
+    "Download file to local machine (use Chrome if it fails on another browser)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 34
+    },
+    "id": "M7b5x8Hr8Yuo",
+    "outputId": "5fbedff6-4a41-47c5-903c-2ad3b59983e1"
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/javascript": [
+       "\n",
+       "    async function download(id, filename, size) {\n",
+       "      if (!google.colab.kernel.accessAllowed) {\n",
+       "        return;\n",
+       "      }\n",
+       "      const div = document.createElement('div');\n",
+       "      const label = document.createElement('label');\n",
+       "      label.textContent = `Downloading \"${filename}\": `;\n",
+       "      div.appendChild(label);\n",
+       "      const progress = document.createElement('progress');\n",
+       "      progress.max = size;\n",
+       "      div.appendChild(progress);\n",
+       "      document.body.appendChild(div);\n",
+       "\n",
+       "      const buffers = [];\n",
+       "      let downloaded = 0;\n",
+       "\n",
+       "      const channel = await google.colab.kernel.comms.open(id);\n",
+       "      // Send a message to notify the kernel that we're ready.\n",
+       "      channel.send({})\n",
+       "\n",
+       "      for await (const message of channel.messages) {\n",
+       "        // Send a message to notify the kernel that we're ready.\n",
+       "        channel.send({})\n",
+       "        if (message.buffers) {\n",
+       "          for (const buffer of message.buffers) {\n",
+       "            buffers.push(buffer);\n",
+       "            downloaded += buffer.byteLength;\n",
+       "            progress.value = downloaded;\n",
+       "          }\n",
+       "        }\n",
+       "      }\n",
+       "      const blob = new Blob(buffers, {type: 'application/binary'});\n",
+       "      const a = document.createElement('a');\n",
+       "      a.href = window.URL.createObjectURL(blob);\n",
+       "      a.download = filename;\n",
+       "      div.appendChild(a);\n",
+       "      a.click();\n",
+       "      div.remove();\n",
+       "    }\n",
+       "  "
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": [
+       "download(\"download_82154b0d-c2b7-4fbd-8f04-e987f3406e7e\", \"5gram_sv_lm.bin\", 1981380707)"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from google.colab import files\n",
+    "files.download(\"5gram_sv_lm.bin\") "
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "name": "train_n-gram_lm_with_KenLM",
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+  },
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