{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From c:\\Users\\olver\\anaconda3\\envs\\NS_env\\Lib\\site-packages\\keras\\src\\losses.py:2976: The name tf.losses.sparse_softmax_cross_entropy is deprecated. Please use tf.compat.v1.losses.sparse_softmax_cross_entropy instead.\n",
      "\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0a6aaf8a708b4826966e824a741b031c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HTML(value='<center> <img\\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.sv…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Cargando las librerias necesarias\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from datasets import load_dataset\n",
    "from transformers import AutoTokenizer\n",
    "from transformers import DataCollatorForSeq2Seq\n",
    "import evaluate\n",
    "from transformers import AutoModelForSeq2SeqLM, Seq2SeqTrainingArguments, Seq2SeqTrainer\n",
    "import numpy as np\n",
    "from datasets import load_metric\n",
    "from huggingface_hub import notebook_login\n",
    "from transformers import pipeline\n",
    "from huggingface_hub import create_repo\n",
    "\n",
    "notebook_login()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RepoUrl('https://huggingface.co/l52mas/spanish_to_ayuuk_translator', endpoint='https://huggingface.co', repo_type='model', repo_id='l52mas/spanish_to_ayuuk_translator')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "repo_id = \"spanish_to_ayuuk_translator\"           \n",
    "organization = \"l52mas\"       \n",
    "\n",
    "create_repo(\n",
    "    repo_id=f\"{organization}/{repo_id}\", \n",
    "    repo_type=\"model\",                  \n",
    "    exist_ok=True                        \n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Leemos los corpus de la biblia y de Delfino\n",
    "bible_data = pd.read_csv('full_corpus_bible.csv')\n",
    "bible_index = pd.read_csv('full_corpus_index.csv')\n",
    "\n",
    "# Unimos ambos corpus y reseteamos los indices\n",
    "bible_data = pd.concat([bible_data, bible_index], axis=0)\n",
    "bible_data['id'] = range(0, len(bible_data))\n",
    "\n",
    "# Guardamos el corpus final\n",
    "bible_data.to_csv('bible_and_corpus1.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f47c85872a8b4f2fbab6c063a8958d8e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Generating train split: 0 examples [00:00, ? examples/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a58d49dd479e4a2b8b23c208c55584e4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Map:   0%|          | 0/10076 [00:00<?, ? examples/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "DatasetDict({\n",
       "    train: Dataset({\n",
       "        features: ['id', 'translation'],\n",
       "        num_rows: 8564\n",
       "    })\n",
       "    test: Dataset({\n",
       "        features: ['id', 'translation'],\n",
       "        num_rows: 1512\n",
       "    })\n",
       "})"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Transformamos el corpus en un dataset de HuggingFace\n",
    "dataset = load_dataset('csv', data_files='bible_and_corpus1.csv', column_names=['spanish', 'ayuuk', 'id'])\n",
    "\n",
    "# Lo transformamos al formato necesario para el entrenamiento\n",
    "dataset = dataset.map(lambda x: {'translation': {'es': x['spanish'], 'ayuuk': x['ayuuk']}, 'id': x['id']})\n",
    "dataset = dataset.remove_columns(['spanish', 'ayuuk'])\n",
    "\n",
    "# Dividimos el dataset en entrenamiento y validación\n",
    "dataset = dataset['train'].train_test_split(test_size=0.15)\n",
    "dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Cargamos el modelo preentrenado\n",
    "checkpoint = \"google-t5/t5-small\"\n",
    "tokenizer = AutoTokenizer.from_pretrained(checkpoint)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "08455684484e4a8eadf18e2d56e67c6e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Map:   0%|          | 0/8564 [00:00<?, ? examples/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5550a7facd3e48f5ac57beda677560f7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Map:   0%|          | 0/1512 [00:00<?, ? examples/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "source_lang = \"es\"\n",
    "target_lang = \"ayuuk\"\n",
    "prefix = \"translate Spanish to Ayuuk: \"\n",
    "\n",
    "# Tranformamos los inputs al formato:\n",
    "# translate Spanish to Ayuuk: texto en español\n",
    "def preprocess_function(examples):\n",
    "    inputs = [prefix + example[source_lang] for example in examples[\"translation\"]]\n",
    "    targets = [example[target_lang] for example in examples[\"translation\"]]\n",
    "    model_inputs = tokenizer(inputs, text_target=targets, max_length=128, truncation=True)\n",
    "    return model_inputs\n",
    "\n",
    "#tokenized_corpus = dataset.map(preprocess_function, batched=True)\n",
    "tokenized_corpus = dataset.map(preprocess_function, batched=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\olver\\AppData\\Local\\Temp\\ipykernel_3180\\3890291550.py:3: FutureWarning: load_metric is deprecated and will be removed in the next major version of datasets. Use 'evaluate.load' instead, from the new library 🤗 Evaluate: https://huggingface.co/docs/evaluate\n",
      "  cer_metric = load_metric(\"cer\")\n",
      "c:\\Users\\olver\\anaconda3\\envs\\NS_env\\Lib\\site-packages\\datasets\\load.py:756: FutureWarning: The repository for cer contains custom code which must be executed to correctly load the metric. You can inspect the repository content at https://raw.githubusercontent.com/huggingface/datasets/2.18.0/metrics/cer/cer.py\n",
      "You can avoid this message in future by passing the argument `trust_remote_code=True`.\n",
      "Passing `trust_remote_code=True` will be mandatory to load this metric from the next major release of `datasets`.\n",
      "  warnings.warn(\n",
      "c:\\Users\\olver\\anaconda3\\envs\\NS_env\\Lib\\site-packages\\datasets\\load.py:756: FutureWarning: The repository for wer contains custom code which must be executed to correctly load the metric. You can inspect the repository content at https://raw.githubusercontent.com/huggingface/datasets/2.18.0/metrics/wer/wer.py\n",
      "You can avoid this message in future by passing the argument `trust_remote_code=True`.\n",
      "Passing `trust_remote_code=True` will be mandatory to load this metric from the next major release of `datasets`.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "data_collator = DataCollatorForSeq2Seq(tokenizer=tokenizer, model=checkpoint)\n",
    "metric = evaluate.load(\"sacrebleu\")\n",
    "cer_metric = load_metric(\"cer\")\n",
    "wer_metric = load_metric(\"wer\")\n",
    "\n",
    "\n",
    "# Función para evaluar el modelo\n",
    "def postprocess_text(preds, labels):\n",
    "    preds = [pred.strip() for pred in preds]\n",
    "    labels = [[label.strip()] for label in labels]\n",
    "\n",
    "    return preds, labels\n",
    "\n",
    "# Función que calcula bleu, cer y wer\n",
    "def compute_metrics(eval_preds):\n",
    "    preds, labels = eval_preds\n",
    "    if isinstance(preds, tuple):\n",
    "        preds = preds[0]\n",
    "    decoded_preds = tokenizer.batch_decode(preds, skip_special_tokens=True)\n",
    "\n",
    "    labels = np.where(labels != -100, labels, tokenizer.pad_token_id)\n",
    "    decoded_labels = tokenizer.batch_decode(labels, skip_special_tokens=True)\n",
    "\n",
    "    decoded_preds, decoded_labels = postprocess_text(decoded_preds, decoded_labels)\n",
    "\n",
    "    result = metric.compute(predictions=decoded_preds, references=decoded_labels)\n",
    "    cer = cer_metric.compute(predictions=decoded_preds, references=decoded_labels)\n",
    "    result[\"cer\"] = cer\n",
    "    \n",
    "    wer =  wer_metric.compute(predictions=decoded_preds, references=decoded_labels)\n",
    "    result[\"wer\"] = wer\n",
    "    \n",
    "    result = {\"bleu\": result[\"score\"], \"cer\": result[\"cer\"], \"wer\": result[\"wer\"]}\n",
    "\n",
    "    prediction_lens = [np.count_nonzero(pred != tokenizer.pad_token_id) for pred in preds]\n",
    "    result[\"gen_len\"] = np.mean(prediction_lens)\n",
    "    result = {k: round(v, 4) for k, v in result.items()}\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#cargamos el modelo preentrenado\n",
    "model = AutoModelForSeq2SeqLM.from_pretrained(checkpoint)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\olver\\anaconda3\\envs\\NS_env\\Lib\\site-packages\\accelerate\\accelerator.py:432: FutureWarning: Passing the following arguments to `Accelerator` is deprecated and will be removed in version 1.0 of Accelerate: dict_keys(['dispatch_batches', 'split_batches', 'even_batches', 'use_seedable_sampler']). Please pass an `accelerate.DataLoaderConfiguration` instead: \n",
      "dataloader_config = DataLoaderConfiguration(dispatch_batches=None, split_batches=False, even_batches=True, use_seedable_sampler=True)\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "# Definimos los argumentos de entrenamiento\n",
    "training_args = Seq2SeqTrainingArguments(\n",
    "    output_dir=\"sp_ay_translator\",\n",
    "    #eval_strategy=\"epoch\",\n",
    "    learning_rate=2e-3,\n",
    "    per_device_train_batch_size=8,\n",
    "    per_device_eval_batch_size=8,\n",
    "    weight_decay=0.0001,\n",
    "    save_total_limit=3,\n",
    "    num_train_epochs=3,\n",
    "    predict_with_generate=True,\n",
    "    fp16=True,\n",
    "    push_to_hub=True,\n",
    ")\n",
    "\n",
    "trainer = Seq2SeqTrainer(\n",
    "    model=model,\n",
    "    args=training_args,\n",
    "    train_dataset=tokenized_corpus[\"train\"],\n",
    "    eval_dataset=tokenized_corpus[\"test\"],\n",
    "    tokenizer=tokenizer,\n",
    "    data_collator=data_collator,\n",
    "    compute_metrics=compute_metrics,\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4e451c4336624bb8bf759873839f8f0c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/3213 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'loss': 2.0331, 'grad_norm': 0.5498889088630676, 'learning_rate': 0.001689386865857454, 'epoch': 0.47}\n",
      "{'loss': 1.6035, 'grad_norm': 0.6067703366279602, 'learning_rate': 0.0013781512605042017, 'epoch': 0.93}\n",
      "{'loss': 1.4596, 'grad_norm': 0.6522427201271057, 'learning_rate': 0.0010669156551509494, 'epoch': 1.4}\n",
      "{'loss': 1.3852, 'grad_norm': 0.48198166489601135, 'learning_rate': 0.0007556800497976969, 'epoch': 1.87}\n",
      "{'loss': 1.3012, 'grad_norm': 0.7035029530525208, 'learning_rate': 0.0004444444444444444, 'epoch': 2.33}\n",
      "{'loss': 1.2695, 'grad_norm': 0.6964818239212036, 'learning_rate': 0.000133208839091192, 'epoch': 2.8}\n",
      "{'train_runtime': 4000.2069, 'train_samples_per_second': 6.423, 'train_steps_per_second': 0.803, 'train_loss': 1.4916166987628385, 'epoch': 3.0}\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\olver\\anaconda3\\envs\\NS_env\\Lib\\site-packages\\transformers\\generation\\utils.py:1132: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8fbd7cc60ecf45a2837a0bc780f3aee2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/189 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "{'eval_loss': 1.221753478050232,\n",
       " 'eval_bleu': 0.1583,\n",
       " 'eval_cer': 0.8668,\n",
       " 'eval_wer': 0.9532,\n",
       " 'eval_gen_len': 18.4861,\n",
       " 'eval_runtime': 135.2724,\n",
       " 'eval_samples_per_second': 11.177,\n",
       " 'eval_steps_per_second': 1.397,\n",
       " 'epoch': 3.0}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Entrenamos y evaluamos el modelo\n",
    "trainer.train()\n",
    "trainer.evaluate()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'translation_text': 'ch, nm ja nm nm n'}]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Ejemplo de traducción\n",
    "text = 'translate Spanish to Ayuuk: Hola, soy Alberto'\n",
    "translator = pipeline(\"translation_xx_to_yy\", model=\"sp_ay_translator\")\n",
    "translator(text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "ename": "HfHubHTTPError",
     "evalue": "403 Client Error: Forbidden for url: https://huggingface.co/l52mas/spanish_to_ayuuk_translator.git/info/lfs/objects/batch (Request ID: Root=1-673bd7f7-49fcc06606e2e5027608f8dc;05b34658-d5f9-4195-a245-09d560630b3d)\n\nAuthorization error.",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mHTTPError\u001b[0m                                 Traceback (most recent call last)",
      "File \u001b[1;32mc:\\Users\\olver\\anaconda3\\envs\\NS_env\\Lib\\site-packages\\huggingface_hub\\utils\\_errors.py:304\u001b[0m, in \u001b[0;36mhf_raise_for_status\u001b[1;34m(response, endpoint_name)\u001b[0m\n\u001b[0;32m    303\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m--> 304\u001b[0m     \u001b[43mresponse\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mraise_for_status\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    305\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m HTTPError \u001b[38;5;28;01mas\u001b[39;00m e:\n",
      "File \u001b[1;32mc:\\Users\\olver\\anaconda3\\envs\\NS_env\\Lib\\site-packages\\requests\\models.py:1021\u001b[0m, in \u001b[0;36mResponse.raise_for_status\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m   1020\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m http_error_msg:\n\u001b[1;32m-> 1021\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m HTTPError(http_error_msg, response\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m)\n",
      "\u001b[1;31mHTTPError\u001b[0m: 403 Client Error: Forbidden for url: https://huggingface.co/l52mas/spanish_to_ayuuk_translator.git/info/lfs/objects/batch",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[1;31mHfHubHTTPError\u001b[0m                            Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[15], line 5\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mhuggingface_hub\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m upload_folder\n\u001b[0;32m      3\u001b[0m folder_path \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m----> 5\u001b[0m \u001b[43mupload_folder\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m      6\u001b[0m \u001b[43m    \u001b[49m\u001b[43mfolder_path\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfolder_path\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m      7\u001b[0m \u001b[43m    \u001b[49m\u001b[43mrepo_id\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43morganization\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m/\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mrepo_id\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m      8\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcommit_message\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mSubiendo modelo de traducción de español a ayuuk\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\n\u001b[0;32m      9\u001b[0m \u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mc:\\Users\\olver\\anaconda3\\envs\\NS_env\\Lib\\site-packages\\huggingface_hub\\utils\\_validators.py:118\u001b[0m, in \u001b[0;36mvalidate_hf_hub_args.<locals>._inner_fn\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    115\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m check_use_auth_token:\n\u001b[0;32m    116\u001b[0m     kwargs \u001b[38;5;241m=\u001b[39m smoothly_deprecate_use_auth_token(fn_name\u001b[38;5;241m=\u001b[39mfn\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m, has_token\u001b[38;5;241m=\u001b[39mhas_token, kwargs\u001b[38;5;241m=\u001b[39mkwargs)\n\u001b[1;32m--> 118\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mc:\\Users\\olver\\anaconda3\\envs\\NS_env\\Lib\\site-packages\\huggingface_hub\\hf_api.py:1227\u001b[0m, in \u001b[0;36mfuture_compatible.<locals>._inner\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1224\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mrun_as_future(fn, \u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m   1226\u001b[0m \u001b[38;5;66;03m# Otherwise, call the function normally\u001b[39;00m\n\u001b[1;32m-> 1227\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mc:\\Users\\olver\\anaconda3\\envs\\NS_env\\Lib\\site-packages\\huggingface_hub\\hf_api.py:4802\u001b[0m, in \u001b[0;36mHfApi.upload_folder\u001b[1;34m(self, repo_id, folder_path, path_in_repo, commit_message, commit_description, token, repo_type, revision, create_pr, parent_commit, allow_patterns, ignore_patterns, delete_patterns, multi_commits, multi_commits_verbose, run_as_future)\u001b[0m\n\u001b[0;32m   4798\u001b[0m     \u001b[38;5;66;03m# Defining a CommitInfo object is not really relevant in this case\u001b[39;00m\n\u001b[0;32m   4799\u001b[0m     \u001b[38;5;66;03m# Let's return early with pr_url only (as string).\u001b[39;00m\n\u001b[0;32m   4800\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m pr_url\n\u001b[1;32m-> 4802\u001b[0m commit_info \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcreate_commit\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m   4803\u001b[0m \u001b[43m    \u001b[49m\u001b[43mrepo_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrepo_type\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   4804\u001b[0m \u001b[43m    \u001b[49m\u001b[43mrepo_id\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrepo_id\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   4805\u001b[0m \u001b[43m    \u001b[49m\u001b[43moperations\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcommit_operations\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   4806\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcommit_message\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcommit_message\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   4807\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcommit_description\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcommit_description\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   4808\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtoken\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtoken\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   4809\u001b[0m \u001b[43m    \u001b[49m\u001b[43mrevision\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrevision\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   4810\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcreate_pr\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcreate_pr\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   4811\u001b[0m \u001b[43m    \u001b[49m\u001b[43mparent_commit\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mparent_commit\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   4812\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   4814\u001b[0m \u001b[38;5;66;03m# Create url to uploaded folder (for legacy return value)\u001b[39;00m\n\u001b[0;32m   4815\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m create_pr \u001b[38;5;129;01mand\u001b[39;00m commit_info\u001b[38;5;241m.\u001b[39mpr_url \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
      "File \u001b[1;32mc:\\Users\\olver\\anaconda3\\envs\\NS_env\\Lib\\site-packages\\huggingface_hub\\utils\\_validators.py:118\u001b[0m, in \u001b[0;36mvalidate_hf_hub_args.<locals>._inner_fn\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    115\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m check_use_auth_token:\n\u001b[0;32m    116\u001b[0m     kwargs \u001b[38;5;241m=\u001b[39m smoothly_deprecate_use_auth_token(fn_name\u001b[38;5;241m=\u001b[39mfn\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m, has_token\u001b[38;5;241m=\u001b[39mhas_token, kwargs\u001b[38;5;241m=\u001b[39mkwargs)\n\u001b[1;32m--> 118\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mc:\\Users\\olver\\anaconda3\\envs\\NS_env\\Lib\\site-packages\\huggingface_hub\\hf_api.py:1227\u001b[0m, in \u001b[0;36mfuture_compatible.<locals>._inner\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1224\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mrun_as_future(fn, \u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m   1226\u001b[0m \u001b[38;5;66;03m# Otherwise, call the function normally\u001b[39;00m\n\u001b[1;32m-> 1227\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mc:\\Users\\olver\\anaconda3\\envs\\NS_env\\Lib\\site-packages\\huggingface_hub\\hf_api.py:3762\u001b[0m, in \u001b[0;36mHfApi.create_commit\u001b[1;34m(self, repo_id, operations, commit_message, commit_description, token, repo_type, revision, create_pr, num_threads, parent_commit, run_as_future)\u001b[0m\n\u001b[0;32m   3759\u001b[0m \u001b[38;5;66;03m# If updating twice the same file or update then delete a file in a single commit\u001b[39;00m\n\u001b[0;32m   3760\u001b[0m _warn_on_overwriting_operations(operations)\n\u001b[1;32m-> 3762\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpreupload_lfs_files\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m   3763\u001b[0m \u001b[43m    \u001b[49m\u001b[43mrepo_id\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrepo_id\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   3764\u001b[0m \u001b[43m    \u001b[49m\u001b[43madditions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43madditions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   3765\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtoken\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtoken\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   3766\u001b[0m \u001b[43m    \u001b[49m\u001b[43mrepo_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrepo_type\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   3767\u001b[0m \u001b[43m    \u001b[49m\u001b[43mrevision\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43munquoted_revision\u001b[49m\u001b[43m,\u001b[49m\u001b[43m  \u001b[49m\u001b[38;5;66;43;03m# first-class methods take unquoted revision\u001b[39;49;00m\n\u001b[0;32m   3768\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcreate_pr\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcreate_pr\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   3769\u001b[0m \u001b[43m    \u001b[49m\u001b[43mnum_threads\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnum_threads\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   3770\u001b[0m \u001b[43m    \u001b[49m\u001b[43mfree_memory\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m  \u001b[49m\u001b[38;5;66;43;03m# do not remove `CommitOperationAdd.path_or_fileobj` on LFS files for \"normal\" users\u001b[39;49;00m\n\u001b[0;32m   3771\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   3772\u001b[0m files_to_copy \u001b[38;5;241m=\u001b[39m _fetch_files_to_copy(\n\u001b[0;32m   3773\u001b[0m     copies\u001b[38;5;241m=\u001b[39mcopies,\n\u001b[0;32m   3774\u001b[0m     repo_type\u001b[38;5;241m=\u001b[39mrepo_type,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   3778\u001b[0m     endpoint\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mendpoint,\n\u001b[0;32m   3779\u001b[0m )\n\u001b[0;32m   3780\u001b[0m commit_payload \u001b[38;5;241m=\u001b[39m _prepare_commit_payload(\n\u001b[0;32m   3781\u001b[0m     operations\u001b[38;5;241m=\u001b[39moperations,\n\u001b[0;32m   3782\u001b[0m     files_to_copy\u001b[38;5;241m=\u001b[39mfiles_to_copy,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   3785\u001b[0m     parent_commit\u001b[38;5;241m=\u001b[39mparent_commit,\n\u001b[0;32m   3786\u001b[0m )\n",
      "File \u001b[1;32mc:\\Users\\olver\\anaconda3\\envs\\NS_env\\Lib\\site-packages\\huggingface_hub\\hf_api.py:4262\u001b[0m, in \u001b[0;36mHfApi.preupload_lfs_files\u001b[1;34m(self, repo_id, additions, token, repo_type, revision, create_pr, num_threads, free_memory, gitignore_content)\u001b[0m\n\u001b[0;32m   4256\u001b[0m     logger\u001b[38;5;241m.\u001b[39minfo(\n\u001b[0;32m   4257\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mSkipped upload for \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mlen\u001b[39m(new_lfs_additions)\u001b[38;5;250m \u001b[39m\u001b[38;5;241m-\u001b[39m\u001b[38;5;250m \u001b[39m\u001b[38;5;28mlen\u001b[39m(new_lfs_additions_to_upload)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m LFS file(s) \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m   4258\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m(ignored by gitignore file).\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m   4259\u001b[0m     )\n\u001b[0;32m   4261\u001b[0m \u001b[38;5;66;03m# Upload new LFS files\u001b[39;00m\n\u001b[1;32m-> 4262\u001b[0m \u001b[43m_upload_lfs_files\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m   4263\u001b[0m \u001b[43m    \u001b[49m\u001b[43madditions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnew_lfs_additions_to_upload\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   4264\u001b[0m \u001b[43m    \u001b[49m\u001b[43mrepo_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrepo_type\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   4265\u001b[0m \u001b[43m    \u001b[49m\u001b[43mrepo_id\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrepo_id\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   4266\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtoken\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtoken\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtoken\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   4267\u001b[0m \u001b[43m    \u001b[49m\u001b[43mendpoint\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mendpoint\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   4268\u001b[0m \u001b[43m    \u001b[49m\u001b[43mnum_threads\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnum_threads\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m   4269\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;66;43;03m# If `create_pr`, we don't want to check user permission on the revision as users with read permission\u001b[39;49;00m\n\u001b[0;32m   4270\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;66;43;03m# should still be able to create PRs even if they don't have write permission on the target branch of the\u001b[39;49;00m\n\u001b[0;32m   4271\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;66;43;03m# PR (i.e. `revision`).\u001b[39;49;00m\n\u001b[0;32m   4272\u001b[0m \u001b[43m    \u001b[49m\u001b[43mrevision\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrevision\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mnot\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mcreate_pr\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[0;32m   4273\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   4274\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m addition \u001b[38;5;129;01min\u001b[39;00m new_lfs_additions_to_upload:\n\u001b[0;32m   4275\u001b[0m     addition\u001b[38;5;241m.\u001b[39m_is_uploaded \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n",
      "File \u001b[1;32mc:\\Users\\olver\\anaconda3\\envs\\NS_env\\Lib\\site-packages\\huggingface_hub\\utils\\_validators.py:118\u001b[0m, in \u001b[0;36mvalidate_hf_hub_args.<locals>._inner_fn\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    115\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m check_use_auth_token:\n\u001b[0;32m    116\u001b[0m     kwargs \u001b[38;5;241m=\u001b[39m smoothly_deprecate_use_auth_token(fn_name\u001b[38;5;241m=\u001b[39mfn\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m, has_token\u001b[38;5;241m=\u001b[39mhas_token, kwargs\u001b[38;5;241m=\u001b[39mkwargs)\n\u001b[1;32m--> 118\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mc:\\Users\\olver\\anaconda3\\envs\\NS_env\\Lib\\site-packages\\huggingface_hub\\_commit_api.py:360\u001b[0m, in \u001b[0;36m_upload_lfs_files\u001b[1;34m(additions, repo_type, repo_id, token, endpoint, num_threads, revision)\u001b[0m\n\u001b[0;32m    358\u001b[0m batch_actions: List[Dict] \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m    359\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m chunk \u001b[38;5;129;01min\u001b[39;00m chunk_iterable(additions, chunk_size\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m256\u001b[39m):\n\u001b[1;32m--> 360\u001b[0m     batch_actions_chunk, batch_errors_chunk \u001b[38;5;241m=\u001b[39m \u001b[43mpost_lfs_batch_info\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    361\u001b[0m \u001b[43m        \u001b[49m\u001b[43mupload_infos\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[43mop\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mupload_info\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mop\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mchunk\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    362\u001b[0m \u001b[43m        \u001b[49m\u001b[43mtoken\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtoken\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    363\u001b[0m \u001b[43m        \u001b[49m\u001b[43mrepo_id\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrepo_id\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    364\u001b[0m \u001b[43m        \u001b[49m\u001b[43mrepo_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrepo_type\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    365\u001b[0m \u001b[43m        \u001b[49m\u001b[43mrevision\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrevision\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    366\u001b[0m \u001b[43m        \u001b[49m\u001b[43mendpoint\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mendpoint\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    367\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    369\u001b[0m     \u001b[38;5;66;03m# If at least 1 error, we do not retrieve information for other chunks\u001b[39;00m\n\u001b[0;32m    370\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m batch_errors_chunk:\n",
      "File \u001b[1;32mc:\\Users\\olver\\anaconda3\\envs\\NS_env\\Lib\\site-packages\\huggingface_hub\\utils\\_validators.py:118\u001b[0m, in \u001b[0;36mvalidate_hf_hub_args.<locals>._inner_fn\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    115\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m check_use_auth_token:\n\u001b[0;32m    116\u001b[0m     kwargs \u001b[38;5;241m=\u001b[39m smoothly_deprecate_use_auth_token(fn_name\u001b[38;5;241m=\u001b[39mfn\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m, has_token\u001b[38;5;241m=\u001b[39mhas_token, kwargs\u001b[38;5;241m=\u001b[39mkwargs)\n\u001b[1;32m--> 118\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mc:\\Users\\olver\\anaconda3\\envs\\NS_env\\Lib\\site-packages\\huggingface_hub\\lfs.py:159\u001b[0m, in \u001b[0;36mpost_lfs_batch_info\u001b[1;34m(upload_infos, token, repo_type, repo_id, revision, endpoint)\u001b[0m\n\u001b[0;32m    157\u001b[0m headers \u001b[38;5;241m=\u001b[39m {\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mLFS_HEADERS, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mbuild_hf_headers(token\u001b[38;5;241m=\u001b[39mtoken \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m)}  \u001b[38;5;66;03m# Token must be provided or retrieved\u001b[39;00m\n\u001b[0;32m    158\u001b[0m resp \u001b[38;5;241m=\u001b[39m get_session()\u001b[38;5;241m.\u001b[39mpost(batch_url, headers\u001b[38;5;241m=\u001b[39mheaders, json\u001b[38;5;241m=\u001b[39mpayload)\n\u001b[1;32m--> 159\u001b[0m \u001b[43mhf_raise_for_status\u001b[49m\u001b[43m(\u001b[49m\u001b[43mresp\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    160\u001b[0m batch_info \u001b[38;5;241m=\u001b[39m resp\u001b[38;5;241m.\u001b[39mjson()\n\u001b[0;32m    162\u001b[0m objects \u001b[38;5;241m=\u001b[39m batch_info\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mobjects\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m)\n",
      "File \u001b[1;32mc:\\Users\\olver\\anaconda3\\envs\\NS_env\\Lib\\site-packages\\huggingface_hub\\utils\\_errors.py:362\u001b[0m, in \u001b[0;36mhf_raise_for_status\u001b[1;34m(response, endpoint_name)\u001b[0m\n\u001b[0;32m    358\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m BadRequestError(message, response\u001b[38;5;241m=\u001b[39mresponse) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01me\u001b[39;00m\n\u001b[0;32m    360\u001b[0m \u001b[38;5;66;03m# Convert `HTTPError` into a `HfHubHTTPError` to display request information\u001b[39;00m\n\u001b[0;32m    361\u001b[0m \u001b[38;5;66;03m# as well (request id and/or server error message)\u001b[39;00m\n\u001b[1;32m--> 362\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m HfHubHTTPError(\u001b[38;5;28mstr\u001b[39m(e), response\u001b[38;5;241m=\u001b[39mresponse) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01me\u001b[39;00m\n",
      "\u001b[1;31mHfHubHTTPError\u001b[0m: 403 Client Error: Forbidden for url: https://huggingface.co/l52mas/spanish_to_ayuuk_translator.git/info/lfs/objects/batch (Request ID: Root=1-673bd7f7-49fcc06606e2e5027608f8dc;05b34658-d5f9-4195-a245-09d560630b3d)\n\nAuthorization error."
     ]
    }
   ],
   "source": [
    "from huggingface_hub import upload_folder\n",
    "\n",
    "folder_path = \".\"\n",
    "\n",
    "upload_folder(\n",
    "    folder_path=folder_path,\n",
    "    repo_id=f\"{organization}/{repo_id}\",\n",
    "    commit_message=\"Subiendo modelo de traducción de español a ayuuk\"\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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