{ "cells": [ { "cell_type": "markdown", "metadata": { "id": "BhqfchJ-f9ZH" }, "source": [ "# Entrenar (fine-tuning) Spanish GPT-2 para generación de texto biblico\n", "### Adaptación del [Colab](https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/language_modeling_from_scratch.ipynb) de Sylvain Gugger" ] }, { "cell_type": "markdown", "metadata": { "id": "dXTtq_OsmvTC" }, "source": [ "- **CLM**: el modelo tiene que predecir el siguiente token en la oración (por lo que las etiquetas son las mismas que las entradas desplazadas hacia la derecha). Para asegurarse de que el modelo no haga trampa, obtiene una máscara de atención que le impedirá acceder a los tokens después del token i cuando intente predecir el token i + 1 en la oración." ] }, { "cell_type": "markdown", "metadata": { "id": "sUQ3G8Bc4Qx3" }, "source": [ "[Probar el modelo](https://huggingface.co/helenpy/spanish-gpt2-finetuned-rap-lyrics-finetuned-biblia)" ] }, { "cell_type": "markdown", "metadata": { "id": "YUUiym-EkmMy" }, "source": [ "### Comprobamos la GPU asignada" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "I-GzsB8vhsR4", "outputId": "e4bf2036-3a31-456b-f7c4-f8610e6437ab" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Tue Mar 24 17:52:47 2026 \n", "+-----------------------------------------------------------------------------------------+\n", "| NVIDIA-SMI 580.82.07 Driver Version: 580.82.07 CUDA Version: 13.0 |\n", "+-----------------------------------------+------------------------+----------------------+\n", "| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |\n", "| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |\n", "| | | MIG M. |\n", "|=========================================+========================+======================|\n", "| 0 Tesla T4 Off | 00000000:00:04.0 Off | 0 |\n", "| N/A 34C P8 9W / 70W | 0MiB / 15360MiB | 0% Default |\n", "| | | N/A |\n", "+-----------------------------------------+------------------------+----------------------+\n", "\n", "+-----------------------------------------------------------------------------------------+\n", "| Processes: |\n", "| GPU GI CI PID Type Process name GPU Memory |\n", "| ID ID Usage |\n", "|=========================================================================================|\n", "| No running processes found |\n", "+-----------------------------------------------------------------------------------------+\n" ] } ], "source": [ "! nvidia-smi" ] }, { "cell_type": "markdown", "metadata": { "id": "H52Y37zK17A2" }, "source": [ "### Autenticación en HF (para compartir modelo)\n", "\n", "Para poder compartir nuestro modelo con la comunidad y generar resultados como el que se muestra en la imagen de arriba a través de la API de inferencia, hay algunos pasos más a seguir.\n", "\n", "Primero debe almacenar su token de autenticación del sitio web HuggingFace (regístrate [aquí] (https://huggingface.co/join) si aún no lo ha hecho), luego ejecute la siguiente celda e ingrese su nombre de usuario y contraseña:" ] }, { "cell_type": "markdown", "metadata": { "id": "_GIe7Q-IkqO4" }, "source": [ "### Instalamos las dependencias requeridas" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "RugU37B-PYjY", "outputId": "a1bc09de-e83e-4f3a-c5af-c3a3859d8a12" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Requirement already satisfied: datasets in /usr/local/lib/python3.12/dist-packages (4.0.0)\n", "Requirement already satisfied: filelock in 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/usr/local/lib/python3.12/dist-packages (from typer->huggingface_hub>=0.21.0->accelerate) (8.3.1)\n", "Requirement already satisfied: shellingham>=1.3.0 in /usr/local/lib/python3.12/dist-packages (from typer->huggingface_hub>=0.21.0->accelerate) (1.5.4)\n", "Requirement already satisfied: rich>=12.3.0 in /usr/local/lib/python3.12/dist-packages (from typer->huggingface_hub>=0.21.0->accelerate) (13.9.4)\n", "Requirement already satisfied: annotated-doc>=0.0.2 in /usr/local/lib/python3.12/dist-packages (from typer->huggingface_hub>=0.21.0->accelerate) (0.0.4)\n", "Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.12/dist-packages (from rich>=12.3.0->typer->huggingface_hub>=0.21.0->accelerate) (4.0.0)\n", "Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.12/dist-packages (from rich>=12.3.0->typer->huggingface_hub>=0.21.0->accelerate) (2.19.2)\n", "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.12/dist-packages (from markdown-it-py>=2.2.0->rich>=12.3.0->typer->huggingface_hub>=0.21.0->accelerate) (0.1.2)\n" ] } ], "source": [ "!pip install datasets\n", "!pip install transformers\n", "!pip install --upgrade accelerate" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 147, "referenced_widgets": [ "e35436ff7a6f4e4e9b3e9cc4b4e3f833", "3b6f9d8a8b124c2ebee4c387a6c2f975", "a69377a298234b319be225b37d3a0ffc", "60426e30454b467c907ba43c43b9afbd", "055c4fb77b1d4b308f19f96458c91ffb", "d9031fce63ca464681a6605149575654", "fa11d13a3929405cb0fc36b0c534439d", "01efab6215f0465690dc214f979cfb67", "23c27895921e4bd6b5cbfd3d764b3b79", "fdc5d6b6b0f24a968c4668b38c636b21", "7a445f2651cf4423999ae1f677468902", "2627770fc0a941e6b27fca13603269fd", "77e47f2ff7864362b0db89ff2526bb31", "b52c4e9ebb384bffb9698db9b280b97c", "8752033739524346ad4654e8b95fb446", "b3a85b22ebce47e5a228bc2d2555eff6", "3ddbd212b37b412d80403e7a26192643", "fef74aad50464efab4961b9d8011733b", "bf8e6cab9c434f159459395c51936775", "f805fa08082e4d21a51dfa85541fcaa9" ] }, "id": "XCwDRj4U1_n_", "outputId": "daf5e129-4357-4476-caf1-32319941d054" }, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "/usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n", "The secret `HF_TOKEN` does not exist in your Colab secrets.\n", "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n", "You will be able to reuse this secret in all of your notebooks.\n", "Please note that authentication is recommended but still optional to access public models or datasets.\n", " warnings.warn(\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "VBox(children=(HTML(value='
\n", " \n", " \n", " \n", " text\n", " \n", " \n", " \n", " \n", " 0\n", " 45 Entonces muchos de los judíos que habían venido para acompañar a María, y vieron lo que hizo Jesús, creyeron en él. 46 Pero algunos de ellos fueron a los fariseos y les dijeron lo que Jesús había hecho. 47 Entonces los principales sacerdotes y los fariseos reunieron el concilio, y dijeron: ¿Qué haremos? Porque este hombre hace muchas señales. 48 Si le dejamos así, todos creerán en él; y vendrán los romanos, y destruirán nuestro lugar santo y nuestra nación. 49 Entonces Caifás, uno de ellos, sumo sacerdote aquel año, les dijo: Vosotros no sabéis nada; 50 ni pensáis que nos conviene que un hombre muera por el pueblo, y no que toda la nación perezca. 51 Esto no lo dijo por sí mismo, sino que como era el sumo sacerdote aquel año, profetizó que Jesús había de morir por la nación; 52 y no solamente por la nación, sino también para congregar en uno a los hijos de Dios que estaban dispersos. 53 Así que, desde aquel día acordaron matarle.\n", " \n", " \n", " 1\n", " 36 Pero si alguno piensa que es impropio para su hija virgen que pase ya de edad, y es necesario que así sea, haga lo que quiera, no peca; que se case. 37 Pero el que está firme en su corazón, sin tener necesidad, sino que es dueño de su propia voluntad, y ha resuelto en su corazón guardar a su hija virgen, bien hace. 38 De manera que el que la da en casamiento hace bien, y el que no la da en casamiento hace mejor.\n", " \n", " \n", " 2\n", " Primera Epístola del Apóstol San Pablo a\n", " \n", " \n", " 3\n", " LUCAS 7\n", " \n", " \n", " 4\n", " 27 ¿Dónde, pues, está la jactancia? Queda excluida. ¿Por cuál ley? ¿Por la de las obras? No, sino por la ley de la fe. 28 Concluimos, pues, que el hombre es justificado por fe sin las obras de la ley. 29 ¿Es Dios solamente Dios de los judíos? ¿No es también Dios de los gentiles? Ciertamente, también de los gentiles. 30 Porque Dios es uno, y él justificará por la fe a los de la circuncisión, y por medio de la fe a los de la incircuncisión. 31 ¿Luego por la fe invalidamos la ley? En ninguna manera, sino que confirmamos la ley.\n", " \n", " \n", " 5\n", " Jesús ora en Getsemaní\n", " \n", " \n", " 6\n", " 25 Pero a medianoche, orando Pablo y Silas, cantaban himnos a Dios; y los presos los oían. 26 Entonces sobrevino de repente un gran terremoto, de tal manera que los cimientos de la cárcel se sacudían; y al instante se abrieron todas las puertas, y las cadenas de todos se soltaron. 27 Despertando el carcelero, y viendo abiertas las puertas de la cárcel, sacó la espada y se iba a matar, pensando que los presos habían huido. 28 Mas Pablo clamó a gran voz, diciendo: No te hagas ningún mal, pues todos estamos aquí. 29 El entonces, pidiendo luz, se precipitó adentro, y temblando, se postró a los pies de Pablo y de Silas; 30 y sacándolos, les dijo: Señores, ¿qué debo hacer para ser salvo? 31 Ellos dijeron: Cree en el Señor Jesucristo, y serás salvo, tú y tu casa. 32 Y le hablaron la palabra del Señor a él y a todos los que estaban en su casa. 33 Y él, tomándolos en aquella misma hora de la noche, les lavó las heridas; y en seguida se bautizó él con todos los suyos. 34 Y llevándolos a su casa, les puso la mesa; y se regocijó con toda su casa de haber creído a Dios.\n", " \n", " \n", " 7\n", " Los gentiles esperarán en él. 13 Y el Dios de esperanza os llene de todo gozo y paz en el creer, para que abundéis en esperanza por el poder del Espíritu Santo.\n", " \n", " \n", " 8\n", " hacer tu voluntad,\n", " \n", " \n", " 9\n", " 7 El aspecto de las langostas era semejante a caballos preparados para la guerra; en las cabezas tenían como coronas de oro; sus caras eran como caras humanas; 8 tenían cabello como cabello de mujer; sus dientes eran como de leones; 9 tenían corazas como corazas de hierro; el ruido de sus alas era como el estruendo de muchos carros de caballos corriendo a la batalla; 10 tenían colas como de escorpiones, y también aguijones; y en sus colas tenían poder para dañar a los hombres durante cinco meses. 11 Y tienen por rey sobre ellos al ángel del abismo, cuyo nombre en hebreo es Abadón, y en griego, Apolión.\n", " \n", " \n", "" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "show_random_elements(datasets[\"train\"])" ] }, { "cell_type": "markdown", "metadata": { "id": "-GlTuQiQo7VK" }, "source": [ "### Tokenización del dataset" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "id": "FtCJmRGlTm1v" }, "outputs": [], "source": [ "from transformers import AutoTokenizer\n", "\n", "tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "id": "Y4N0s8OxqgWW" }, "outputs": [], "source": [ "tokenizer._tokenizer.save(\"tokenizer.json\")" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "id": "XvFTOOthbnLm" }, "outputs": [], "source": [ "def tokenize_fn(examples):\n", " return tokenizer(examples[\"text\"])" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 81, "referenced_widgets": [ "316860ef062241089da19ec74dac0381", "e05fcba837ee4db6ac61ccbe0e56514c", "558e5c3c909143398cb5ec585f2b6734", "72d8ea0f59b542d08fe3c8cc97365f6c", "4ff23f3a9560429d866586f22c08a7fd", "d6f858e5c77340be9d0a0de4041661dd", "2538573a7d8846f6b7d38a5e0de6b44b", "dd49b4fc472b478d9c11f45a0662f034", "b2ac3e6996eb4d67996731f04c686d2b", "10bc112cff304a11a2edbd86a8232416", "0eb04b6f719848d4942a08c0adfc9376", "b11fd07903ad44e7bd845fc247f75078", "e8c05c577c92426bbb457e7946dd8b7c", "ae107390639946d7806ae793805dc202", "896ab2d1cf8c495f85ca04fb509e25c9", "f29ddda499f648ef920de3b174cf8b9b", "0592b5af8a0f46908a5c56ef7166f603", "14eeea5515134407a94e1a6796166cc2", "941cb3087a9a433d890b8d772a37c583", "4352750ae8694920a0aabe12f1e12cf6", "81126fff67eb40de9d274cf655a048ec", "a1b31c0cad8d4e08a67def09a9349764" ] }, "id": "sbiWdAqcbvLJ", "outputId": "f455eb89-75f2-49a4-cc15-ae4ed988c8e0" }, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Map: 0%| | 0/3083 [00:00" ], "text/html": [ "\n", "
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\n", " \n", " \n", " [281/603 01:27 < 01:41, 3.18 it/s, Epoch 1.39/3]\n", "
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EpochTraining LossValidation Loss
1No log2.401889

" ] }, "metadata": {} }, { "output_type": "error", "ename": "KeyboardInterrupt", "evalue": "", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", "\u001b[0;32m/tmp/ipykernel_1551/4032920361.py\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mtrainer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtrain\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[0;32m/usr/local/lib/python3.12/dist-packages/transformers/trainer.py\u001b[0m in \u001b[0;36mtrain\u001b[0;34m(self, resume_from_checkpoint, trial, ignore_keys_for_eval)\u001b[0m\n\u001b[1;32m 2163\u001b[0m \u001b[0;31m# Disable progress bars when uploading models during checkpoints to avoid polluting stdout\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2164\u001b[0m \u001b[0mhf_hub_utils\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdisable_progress_bars\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2165\u001b[0;31m return inner_training_loop(\n\u001b[0m\u001b[1;32m 2166\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2167\u001b[0m \u001b[0mresume_from_checkpoint\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mresume_from_checkpoint\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.12/dist-packages/transformers/trainer.py\u001b[0m in \u001b[0;36m_inner_training_loop\u001b[0;34m(self, batch_size, args, resume_from_checkpoint, trial, ignore_keys_for_eval)\u001b[0m\n\u001b[1;32m 2539\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlogging_nan_inf_filter\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2540\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mis_torch_xla_available\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2541\u001b[0;31m \u001b[0;32mand\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0misnan\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtr_loss_step\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0misinf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtr_loss_step\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 2542\u001b[0m ):\n\u001b[1;32m 2543\u001b[0m \u001b[0;31m# if loss is nan or inf simply add the average of previous logged losses\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mKeyboardInterrupt\u001b[0m: " ] } ], "source": [ "trainer.train()" ] }, { "cell_type": "code", "execution_count": 47, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 57 }, "id": "JHTcfB5Ge805", "outputId": "be8ecfc3-2a50-4d5a-95ab-a865cb460b7e" }, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "\n", "

\n", " \n", " \n", " [23/23 00:02]\n", "
\n", " " ] }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ "Perplexity: 11.68\n" ] } ], "source": [ "import math\n", "eval_results = trainer.evaluate()\n", "print(f\"Perplexity: {math.exp(eval_results['eval_loss']):.2f}\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 197, "referenced_widgets": [ "77a4206770694ce7a84461f4d2229fd4", "2281579f775d430b9e476e09fa07960f", "7ed10133f60a4f80818db5bf8c462260", "77c9385278504246a13d0d0f915dd00e", "3073efdc7f824bfca0bee41d065f440f", "8514ecfdca83497cb26ad21f17d8f6a3", "88e1407716914a928ccb0282e2de5610", "0b5efdcf74c1461c91b30129049726e5", "81fcd36dde7249738dd62b2fb3f2d32e", "62a2351a0c4144ceb4892ac72c2fd7a0", "adad5183ab4d45d294ebbc2d825e2183", "c8192737d38c411d9ffa515e5976b991", "e7c66a3a9401400d82644b69ba8e44f1", "d44ccc65088c4bb9b4da123c058e48a0", "c0fcf58fbad442c6a39a21d40354f051", "9c0c9f9d6f914fef842e6b0deab68b89", "c69b1623ca134a9a9a77bf221a94e93a", "445b622297334e2e971b406f8d7cfe8e", "68f11d839fab462f9001375446bd3e1b", "67ba2284d8944caeb04626c1801eea55", "16000517d44f43e0a507fd0a2827e675", "b2dd4706e8d34d6cb379ff3fc3378fb2" ] }, "id": "52W8UhIUlSTI", "outputId": "8ec73fe0-72c3-4c8b-e47f-8a3c4dc60e4f" }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "77a4206770694ce7a84461f4d2229fd4", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Upload file runs/May24_04-19-35_53f192422586/events.out.tfevents.1684901988.53f192422586.21913.11: 0%| …" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "c8192737d38c411d9ffa515e5976b991", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Upload file runs/May24_04-19-35_53f192422586/events.out.tfevents.1684902239.53f192422586.21913.13: 0%| …" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "text": [ "To https://huggingface.co/helenpy/spanish-gpt2-finetuned-rap-lyrics-finetuned-biblia\n", " b063177..47a0928 main -> main\n", "\n", "WARNING:huggingface_hub.repository:To https://huggingface.co/helenpy/spanish-gpt2-finetuned-rap-lyrics-finetuned-biblia\n", " b063177..47a0928 main -> main\n", "\n" ] }, { "data": { "application/vnd.google.colaboratory.intrinsic+json": { "type": "string" }, "text/plain": [ "'https://huggingface.co/helenpy/spanish-gpt2-finetuned-rap-lyrics-finetuned-biblia/commit/47a0928fe5d098157c626544619cdb4d073b22f9'" ] }, "execution_count": 116, "metadata": {}, "output_type": "execute_result" } ], "source": [ "trainer.push_to_hub()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "wqD6TPo88ibx", "outputId": "ee03117a-66fa-40d7-c67d-61f7dea83899" }, "outputs": [ { "data": { "text/plain": [ "CommitInfo(commit_url='https://huggingface.co/helenpy/spanish-gpt2-finetuned-rap-lyrics-finetuned-biblia/commit/6c4166b2fb2ee3a50b51750eba342f87860b0072', commit_message='Upload tokenizer', commit_description='', oid='6c4166b2fb2ee3a50b51750eba342f87860b0072', pr_url=None, pr_revision=None, pr_num=None)" ] }, "execution_count": 117, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tokenizer.push_to_hub(f\"{model_name}-finetuned-biblia\")" ] }, { "cell_type": "markdown", "source": [ "### Probar el modelo fine-tuneado" ], "metadata": { "id": "eVVk-ck-Ge--" } }, { "cell_type": "code", "source": [ "from transformers import pipeline\n", "\n", "generator_old = pipeline('text-generation', model='Narrativa/spanish-gpt2-finetuned-rap-lyrics', tokenizer='Narrativa/spanish-gpt2-finetuned-rap-lyrics')\n", "generator_new = pipeline('text-generation', model='helenpy/spanish-gpt2-finetuned-rap-lyrics-finetuned-biblia', tokenizer='helenpy/spanish-gpt2-finetuned-rap-lyrics-finetuned-biblia')\n", "\n", "# Generar texto\n", "# Puedes cambiar el prompt para probar diferentes inicios\n", "prompt = \"Estamos hoy en la clase\"\n", "num_return_sequences = 3\n", "max_length = 50\n" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000, "referenced_widgets": [ "528482665cfc40d7a208c297e92e78e0", "380c1b7f421a46cfba446076041921b8", "b5b71a2418ae40c7bd505ae5cd197d38", "490c369e46034887a4fd0063506b6273", "958951c7862f47c1a841381e9a01b733", "2971d0d854e34f3ab45366aa18056d58", "55eda4711f1f435eb131edfe99d4e018", "5488f78e48ef46e599576c8affaf39c2", "bcaee66b33974fe1941a24bb3bdd0df8", "3189445e230a4d618cc28779e84bf185", "9842af4827084901b29c32c764d6a64b", "6da26f659f574f82a123e8b159adab0d", "eb8e1a47d93f4cd695a70c093767a740", "b3d1515752ae468bbe9c2832108b7dec", "2b9befd6784a4f7fa7833a334a2a7e88", "63843de9f7354b11877f0272f8db68e5", "307551e0b16f443fb141ae1bba2ca412", 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