{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing nlx-92431870-9d3d-11ed-9c6a-05e960837f89.wav\n",
      "Original sample rate: 44100\n",
      "Resampled sample rate: 16000\n",
      "Processing nlx-724565f0-9d3d-11ed-9b2b-fb45fabf3581.wav\n",
      "Original sample rate: 44100\n",
      "Resampled sample rate: 16000\n",
      "Processing nlx-01862d90-9d3d-11ed-ade0-33dea1872c08.wav\n",
      "Original sample rate: 44100\n",
      "Resampled sample rate: 16000\n",
      "Processing nlx-e1988b30-9d3d-11ed-9002-73f4e94ec541.wav\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/vit-ap/anaconda3/lib/python3.7/site-packages/torchaudio/functional/functional.py:540: UserWarning: At least one mel filterbank has all zero values. The value for `n_mels` (128) may be set too high. Or, the value for `n_freqs` (201) may be set too low.\n",
      "  \"At least one mel filterbank has all zero values. \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original sample rate: 44100\n",
      "Resampled sample rate: 16000\n",
      "Processing nlx-4af2b7a0-9d3d-11ed-8cf7-792f71ad5e87.wav\n",
      "Original sample rate: 44100\n",
      "Resampled sample rate: 16000\n",
      "Processing nlx-c5144800-9d3d-11ed-8cf7-792f71ad5e87.wav\n",
      "Original sample rate: 44100\n",
      "Resampled sample rate: 16000\n",
      "Processing nlx-970eaa40-9d3d-11ed-9002-73f4e94ec541.wav\n",
      "Original sample rate: 44100\n",
      "Resampled sample rate: 16000\n",
      "Processing nlx-20ad0810-9d3d-11ed-8cf7-792f71ad5e87.wav\n",
      "Original sample rate: 44100\n",
      "Resampled sample rate: 16000\n",
      "Processing nlx-9d1b15f0-9d3c-11ed-aefd-7de9011dbebd.wav\n",
      "Original sample rate: 44100\n",
      "Resampled sample rate: 16000\n",
      "Processing nlx-b5db9a60-9d3c-11ed-9c6a-05e960837f89.wav\n",
      "Original sample rate: 44100\n",
      "Resampled sample rate: 16000\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import torch\n",
    "import torchaudio\n",
    "\n",
    "def preprocess_audio(audio_path):\n",
    "    # Load the audio file\n",
    "    waveform, sr = torchaudio.load(audio_path)\n",
    "\n",
    "    # Print original sample rate\n",
    "    print(f'Original sample rate: {sr}')\n",
    "\n",
    "    # Resample to 16kHz\n",
    "    if sr != 16000:\n",
    "        resampler = torchaudio.transforms.Resample(sr, 16000)\n",
    "        waveform = resampler(waveform)\n",
    "        sr = 16000\n",
    "\n",
    "    # Print resampled sample rate\n",
    "    print(f'Resampled sample rate: {sr}')\n",
    "\n",
    "    # Define the normalization and feature extraction transformation\n",
    "    transform = torchaudio.transforms.MFCC(sample_rate=sr, n_mfcc=40)\n",
    "\n",
    "    # Normalize and extract features from the audio\n",
    "    mfcc = transform(waveform)\n",
    "\n",
    "    # Prepare the tensor for fine-tuning\n",
    "    tensor = mfcc.squeeze(0)\n",
    "    tensor = tensor.transpose(0, 1)\n",
    "\n",
    "    return tensor\n",
    "\n",
    "path_audio = '/home/vit-ap/Desktop/Navana AI Intern/AudioRecordings'\n",
    "\n",
    "for filename in os.listdir(path_audio):\n",
    "    if filename.endswith('.wav'):\n",
    "        full_path = os.path.join(path_audio, filename)\n",
    "        print(f'Processing {filename}')\n",
    "        tensor = preprocess_audio(full_path)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Token is valid.\n",
      "\u001b[1m\u001b[31mCannot authenticate through git-credential as no helper is defined on your machine.\n",
      "You might have to re-authenticate when pushing to the Hugging Face Hub.\n",
      "Run the following command in your terminal in case you want to set the 'store' credential helper as default.\n",
      "\n",
      "git config --global credential.helper store\n",
      "\n",
      "Read https://git-scm.com/book/en/v2/Git-Tools-Credential-Storage for more details.\u001b[0m\n",
      "Token has not been saved to git credential helper.\n",
      "Your token has been saved to /home/vit-ap/.cache/huggingface/token\n",
      "Login successful\n"
     ]
    }
   ],
   "source": [
    "from huggingface_hub import notebook_login\n",
    "\n",
    "notebook_login()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1;31mE: \u001b[0mCould not open lock file /var/lib/dpkg/lock-frontend - open (13: Permission denied)\u001b[0m\r\n",
      "\u001b[1;31mE: \u001b[0mUnable to acquire the dpkg frontend lock (/var/lib/dpkg/lock-frontend), are you root?\u001b[0m\r\n"
     ]
    }
   ],
   "source": [
    "!apt install git-lfs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking in links: https://download.pytorch.org/whl/cu110/torch_stable.html\n",
      "Requirement already satisfied: torchaudio in /home/vit-ap/anaconda3/lib/python3.7/site-packages (0.12.1)\n",
      "Requirement already satisfied: torch==1.12.1 in /home/vit-ap/anaconda3/lib/python3.7/site-packages (from torchaudio) (1.12.1)\n",
      "Requirement already satisfied: typing-extensions in /home/vit-ap/anaconda3/lib/python3.7/site-packages (from torch==1.12.1->torchaudio) (4.3.0)\n",
      "\u001b[31mERROR: Could not find a version that satisfies the requirement wav2vec2-gpu (from versions: none)\u001b[0m\n",
      "\u001b[31mERROR: No matching distribution found for wav2vec2-gpu\u001b[0m\n",
      "Collecting git+https://github.com/pytorch/fairseq\n",
      "  Cloning https://github.com/pytorch/fairseq to /tmp/pip-req-build-6m2gl03y\n",
      "  Running command git clone -q https://github.com/pytorch/fairseq /tmp/pip-req-build-6m2gl03y\n",
      "  Running command git submodule update --init --recursive -q\n",
      "  Installing build dependencies ... \u001b[?25lerror\n",
      "\u001b[31m  ERROR: Command errored out with exit status -9:\n",
      "   command: /home/vit-ap/anaconda3/bin/python /home/vit-ap/anaconda3/lib/python3.7/site-packages/pip install --ignore-installed --no-user --prefix /tmp/pip-build-env-oaw0b2ig/overlay --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- 'setuptools>=18.0' wheel cython 'numpy>=1.21.3' 'torch>=1.10'\n",
      "       cwd: None\n",
      "  Complete output (9 lines):\n",
      "  Collecting setuptools>=18.0\n",
      "    Using cached setuptools-66.1.1-py3-none-any.whl (1.3 MB)\n",
      "  Collecting wheel\n",
      "    Using cached wheel-0.38.4-py3-none-any.whl (36 kB)\n",
      "  Collecting cython\n",
      "    Using cached Cython-0.29.33-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl (1.9 MB)\n",
      "  Collecting numpy>=1.21.3\n",
      "    Using cached numpy-1.21.6-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (15.7 MB)\n",
      "  Collecting torch>=1.10\n",
      "  ----------------------------------------\u001b[0m\n",
      "\u001b[31mERROR: Command errored out with exit status -9: /home/vit-ap/anaconda3/bin/python /home/vit-ap/anaconda3/lib/python3.7/site-packages/pip install --ignore-installed --no-user --prefix /tmp/pip-build-env-oaw0b2ig/overlay --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- 'setuptools>=18.0' wheel cython 'numpy>=1.21.3' 'torch>=1.10' Check the logs for full command output.\u001b[0m\n",
      "\u001b[?25h"
     ]
    }
   ],
   "source": [
    "!pip install torchaudio -f https://download.pytorch.org/whl/cu110/torch_stable.html\n",
    "!pip install wav2vec2-gpu\n",
    "!pip install git+https://github.com/pytorch/fairseq\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "ename": "OSError",
     "evalue": "wav2vec2-base is not a local folder and is not a valid model identifier listed on 'https://huggingface.co/models'\nIf this is a private repository, make sure to pass a token having permission to this repo with `use_auth_token` or log in with `huggingface-cli login` and pass `use_auth_token=True`.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mHTTPError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/huggingface_hub/utils/_errors.py\u001b[0m in \u001b[0;36mhf_raise_for_status\u001b[0;34m(response, endpoint_name)\u001b[0m\n\u001b[1;32m    263\u001b[0m     \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 264\u001b[0;31m         \u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mraise_for_status\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    265\u001b[0m     \u001b[0;32mexcept\u001b[0m \u001b[0mHTTPError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/requests/models.py\u001b[0m in \u001b[0;36mraise_for_status\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    939\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mhttp_error_msg\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 940\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mHTTPError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhttp_error_msg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\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    941\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mHTTPError\u001b[0m: 404 Client Error: Not Found for url: https://huggingface.co/wav2vec2-base/resolve/main/config.json",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[0;31mRepositoryNotFoundError\u001b[0m                   Traceback (most recent call last)",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/transformers/utils/hub.py\u001b[0m in \u001b[0;36mcached_file\u001b[0;34m(path_or_repo_id, filename, cache_dir, force_download, resume_download, proxies, use_auth_token, revision, local_files_only, subfolder, user_agent, _raise_exceptions_for_missing_entries, _raise_exceptions_for_connection_errors, _commit_hash)\u001b[0m\n\u001b[1;32m    419\u001b[0m             \u001b[0muse_auth_token\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0muse_auth_token\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 420\u001b[0;31m             \u001b[0mlocal_files_only\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlocal_files_only\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    421\u001b[0m         )\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/huggingface_hub/utils/_validators.py\u001b[0m in \u001b[0;36m_inner_fn\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    123\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 124\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\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    125\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/huggingface_hub/file_download.py\u001b[0m in \u001b[0;36mhf_hub_download\u001b[0;34m(repo_id, filename, subfolder, repo_type, revision, library_name, library_version, cache_dir, user_agent, force_download, force_filename, proxies, etag_timeout, resume_download, token, local_files_only, legacy_cache_layout)\u001b[0m\n\u001b[1;32m   1108\u001b[0m                     \u001b[0mproxies\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mproxies\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1109\u001b[0;31m                     \u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0metag_timeout\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   1110\u001b[0m                 )\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/huggingface_hub/utils/_validators.py\u001b[0m in \u001b[0;36m_inner_fn\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    123\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 124\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\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    125\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/huggingface_hub/file_download.py\u001b[0m in \u001b[0;36mget_hf_file_metadata\u001b[0;34m(url, token, proxies, timeout)\u001b[0m\n\u001b[1;32m   1439\u001b[0m     )\n\u001b[0;32m-> 1440\u001b[0;31m     \u001b[0mhf_raise_for_status\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mr\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   1441\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/huggingface_hub/utils/_errors.py\u001b[0m in \u001b[0;36mhf_raise_for_status\u001b[0;34m(response, endpoint_name)\u001b[0m\n\u001b[1;32m    305\u001b[0m             )\n\u001b[0;32m--> 306\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mRepositoryNotFoundError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmessage\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    307\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mRepositoryNotFoundError\u001b[0m: 404 Client Error. (Request ID: Root=1-63d2393f-1eb57d6f7b59d4c0691b41d5)\n\nRepository Not Found for url: https://huggingface.co/wav2vec2-base/resolve/main/config.json.\nPlease make sure you specified the correct `repo_id` and `repo_type`.\nIf you are trying to access a private or gated repo, make sure you are authenticated.",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mOSError\u001b[0m                                   Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-29-87607d67bd9c>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;31m# Load the model and tokenizer\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0mmodel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mAutoModelWithLMHead\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfrom_pretrained\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"wav2vec2-base\"\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      7\u001b[0m \u001b[0mtokenizer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mAutoTokenizer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfrom_pretrained\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"wav2vec2-base\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      8\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/transformers/models/auto/modeling_auto.py\u001b[0m in \u001b[0;36mfrom_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, *model_args, **kwargs)\u001b[0m\n\u001b[1;32m   1252\u001b[0m             \u001b[0mFutureWarning\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1253\u001b[0m         )\n\u001b[0;32m-> 1254\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfrom_pretrained\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpretrained_model_name_or_path\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0mmodel_args\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/transformers/models/auto/auto_factory.py\u001b[0m in \u001b[0;36mfrom_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, *model_args, **kwargs)\u001b[0m\n\u001b[1;32m    437\u001b[0m                 \u001b[0mtrust_remote_code\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtrust_remote_code\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    438\u001b[0m                 \u001b[0;34m**\u001b[0m\u001b[0mhub_kwargs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 439\u001b[0;31m                 \u001b[0;34m**\u001b[0m\u001b[0mkwargs\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    440\u001b[0m             )\n\u001b[1;32m    441\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mhasattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"auto_map\"\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mcls\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mauto_map\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/transformers/models/auto/configuration_auto.py\u001b[0m in \u001b[0;36mfrom_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, **kwargs)\u001b[0m\n\u001b[1;32m    850\u001b[0m         \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"name_or_path\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpretrained_model_name_or_path\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    851\u001b[0m         \u001b[0mtrust_remote_code\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"trust_remote_code\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 852\u001b[0;31m         \u001b[0mconfig_dict\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0munused_kwargs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mPretrainedConfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_config_dict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpretrained_model_name_or_path\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\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    853\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;34m\"auto_map\"\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mconfig_dict\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;34m\"AutoConfig\"\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mconfig_dict\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"auto_map\"\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    854\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mtrust_remote_code\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/transformers/configuration_utils.py\u001b[0m in \u001b[0;36mget_config_dict\u001b[0;34m(cls, pretrained_model_name_or_path, **kwargs)\u001b[0m\n\u001b[1;32m    563\u001b[0m         \u001b[0moriginal_kwargs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdeepcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    564\u001b[0m         \u001b[0;31m# Get config dict associated with the base config file\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 565\u001b[0;31m         \u001b[0mconfig_dict\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwargs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcls\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_config_dict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpretrained_model_name_or_path\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\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    566\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;34m\"_commit_hash\"\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mconfig_dict\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    567\u001b[0m             \u001b[0moriginal_kwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"_commit_hash\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconfig_dict\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"_commit_hash\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/transformers/configuration_utils.py\u001b[0m in \u001b[0;36m_get_config_dict\u001b[0;34m(cls, pretrained_model_name_or_path, **kwargs)\u001b[0m\n\u001b[1;32m    630\u001b[0m                     \u001b[0mrevision\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mrevision\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    631\u001b[0m                     \u001b[0msubfolder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msubfolder\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 632\u001b[0;31m                     \u001b[0m_commit_hash\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcommit_hash\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    633\u001b[0m                 )\n\u001b[1;32m    634\u001b[0m                 \u001b[0mcommit_hash\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mextract_commit_hash\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresolved_config_file\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcommit_hash\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/transformers/utils/hub.py\u001b[0m in \u001b[0;36mcached_file\u001b[0;34m(path_or_repo_id, filename, cache_dir, force_download, resume_download, proxies, use_auth_token, revision, local_files_only, subfolder, user_agent, _raise_exceptions_for_missing_entries, _raise_exceptions_for_connection_errors, _commit_hash)\u001b[0m\n\u001b[1;32m    423\u001b[0m     \u001b[0;32mexcept\u001b[0m \u001b[0mRepositoryNotFoundError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    424\u001b[0m         raise EnvironmentError(\n\u001b[0;32m--> 425\u001b[0;31m             \u001b[0;34mf\"{path_or_repo_id} is not a local folder and is not a valid model identifier \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    426\u001b[0m             \u001b[0;34m\"listed on 'https://huggingface.co/models'\\nIf this is a private repository, make sure to \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    427\u001b[0m             \u001b[0;34m\"pass a token having permission to this repo with `use_auth_token` or log in with \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mOSError\u001b[0m: wav2vec2-base is not a local folder and is not a valid model identifier listed on 'https://huggingface.co/models'\nIf this is a private repository, make sure to pass a token having permission to this repo with `use_auth_token` or log in with `huggingface-cli login` and pass `use_auth_token=True`."
     ]
    }
   ],
   "source": [
    "import torch\n",
    "from transformers import AutoModelWithLMHead, AutoTokenizer\n",
    "\n",
    "\n",
    "# Load the model and tokenizer\n",
    "model = AutoModelWithLMHead.from_pretrained(\"wav2vec2-base\")\n",
    "tokenizer = AutoTokenizer.from_pretrained(\"wav2vec2-base\")\n",
    "\n",
    "# Move the model to the CPU\n",
    "model.to(\"cpu\")\n",
    "\n",
    "# Set the model in evaluation mode\n",
    "model.eval()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/vit-ap/anaconda3/lib/python3.7/site-packages/transformers/models/auto/modeling_auto.py:1252: FutureWarning: The class `AutoModelWithLMHead` is deprecated and will be removed in a future version. Please use `AutoModelForCausalLM` for causal language models, `AutoModelForMaskedLM` for masked language models and `AutoModelForSeq2SeqLM` for encoder-decoder models.\n",
      "  FutureWarning,\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model wav2vec2-base is not available.\n"
     ]
    }
   ],
   "source": [
    "from transformers import pipeline, AutoModelWithLMHead\n",
    "\n",
    "MODEL_NAME = \"wav2vec2-base\"\n",
    "try:\n",
    "    model = AutoModelWithLMHead.from_pretrained(MODEL_NAME)\n",
    "    print(f\"Model {MODEL_NAME} is available.\")\n",
    "except:\n",
    "    print(f\"Model {MODEL_NAME} is not available.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model wav2vec2-base is not available.\n"
     ]
    }
   ],
   "source": [
    "from transformers import pipeline, AutoModelWithLMHead\n",
    "\n",
    "MODEL_NAME = \"wav2vec2-base\"\n",
    "try:\n",
    "    model = AutoModelWithLMHead.from_pretrained(MODEL_NAME)\n",
    "    print(f\"Model {MODEL_NAME} is available.\")\n",
    "except:\n",
    "    print(f\"Model {MODEL_NAME} is not available.\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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