Subiendo el modelo Spanish-F5-TTS

README.md

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+---
+license: cc-by-nc-4.0
+library_name: f5-tts
+language:
+- es
+base_model:
+- SWivid/F5-TTS
+---
+
+# [GitHub](https://github.com/jpgallegoar/Spanish-F5)
+
+# F5-TTS Spanish Language Model
+
+## Overview
+The F5-TTS model is finetuned specifically for Spanish language speech synthesis. This project aims to deliver high-quality, regionally diverse speech synthesis capabilities for Spanish speakers.
+
+## License
+This model is released under the CC0-1.0 license, which allows for free usage, modification, and distribution.
+
+## Datasets
+The following datasets were used for training:
+
+- [Voxpopuli Dataset](https://huggingface.co/datasets/facebook/voxpopuli), with mainly Peninsular Spain accents
+- Crowdsourced high-quality Spanish speech data:
+  - Argentinian Spanish
+  - Chilean Spanish
+  - Colombian Spanish
+  - Peruvian Spanish
+  - Puerto Rican Spanish
+  - Venezuelan Spanish
+- TEDx Spanish Corpus
+
+
+Additional sources:
+- [Crowdsourced high-quality Argentinian Spanish speech data set](https://www.openslr.org/61/)
+- [Crowdsourced high-quality Chilean Spanish speech data set](https://www.openslr.org/71/)
+- [Crowdsourced high-quality Colombian Spanish speech data set](https://www.openslr.org/72/)
+- [Crowdsourced high-quality Peruvian Spanish speech data set](https://www.openslr.org/73/)
+- [Crowdsourced high-quality Puerto Rico Spanish speech data set](https://www.openslr.org/74/)
+- [Crowdsourced high-quality Venezuelan Spanish speech data set](https://www.openslr.org/75/)
+- - [TEDx Spanish Corpus](https://www.openslr.org/67/)
+
+
+## Model Information
+**Base Model:** SWivid/F5-TTS  
+**Total Training Duration:** 218 hours of audio  
+**Training Configuration:**
+- Batch Size: 3200
+- Max Samples: 64
+- Training Steps: 1,200,000
+
+## Usage Instructions
+
+### Method 0: HuggingFace space (https://huggingface.co/spaces/jpgallegoar/Spanish-F5)
+
+### Method 1: Manual Model Replacement
+
+1. **Run the F5-TTS Application:** Start the F5-TTS application and observe the terminal for output indicating the model file path. It should appear similar to:
+   ```
+   model : C:\Users\thega\.cache\huggingface\hub\models--SWivid--F5-TTS\snapshots\995ff41929c08ff968786b448a384330438b5cb6\F5TTS_Base\model_1200000.safetensors
+   ```
+2. **Replace the Model File:**
+   - Navigate to the displayed file location.
+   - Rename the existing model file to `model_1200000.safetensors.bak`.
+   - Download `model_1200000.safetensors` from this repository and save it to the same location.
+
+3. **Restart the Application:** Relaunch the F5-TTS application to load the updated model.
+
+### Alternative Methods
+
+- **GitHub Repository:** Clone the [Spanish-F5 repository](https://github.com/jpgallegoar/Spanish-F5/) and follow the provided installation instructions.
+- **Google Colab:** Use the model via [Google Colab](https://colab.research.google.com/drive/1mm4NAlZVZq2_oL6ftijY64-PeEYwnqG1?usp=sharing).
+  - Runtime -> Change Runtime Type -> T4 GPU
+  - Runtime -> Run all
+  - Click on the link shown in "Running on public URL: https://link.gradio.live" when it loads
+- **Jupyter Notebook:** Run the model through the `Spanish_F5.ipynb` notebook.
+
+## Contributions and Recommendations
+This model may benefit from further fine-tuning to enhance its performance across different Spanish dialects. Contributions from the community are encouraged. For optimal output quality, preprocess the reference audio by removing background noise, balancing audio levels, and enhancing clarity.

Spanish_F5.ipynb

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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "0-duLUr_Iema",
+        "outputId": "615d30a6-2a04-4859-ad9d-79edd6a3ffc1"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
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+            "\u001b[?25hDownloading websockets-12.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (130 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m130.2/130.2 kB\u001b[0m \u001b[31m6.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hBuilding wheels for collected packages: f5-tts, transformers-stream-generator, encodec\n",
+            "  Building wheel for f5-tts (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for f5-tts: filename=f5_tts-0.0.0-py3-none-any.whl size=1280758 sha256=b900d02175b3eccb21dec0d1801d9bffc4fd30451509a67ef45a6f0653580c7c\n",
+            "  Stored in directory: /tmp/pip-ephem-wheel-cache-3_lciyxv/wheels/63/43/c5/fb04687e74a83e9bc15bb575c33e53b6aca4bf7a2fb32982f2\n",
+            "  Building wheel for transformers-stream-generator (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for transformers-stream-generator: filename=transformers_stream_generator-0.0.5-py3-none-any.whl size=12425 sha256=0e9f6ab066ff4bcfa59962bd47464e4dc82ea27afed7086565aad6d86b0b6e5b\n",
+            "  Stored in directory: /root/.cache/pip/wheels/95/4a/90/140f7b67d125906f6a165f38aad212ecb4a695ad0d87582437\n",
+            "  Building wheel for encodec (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for encodec: filename=encodec-0.1.1-py3-none-any.whl size=45760 sha256=bccc14b58f86cf341371dda33deedf0bd6ef90e06649662b5337eb0e9e785a92\n",
+            "  Stored in directory: /root/.cache/pip/wheels/fc/36/cb/81af8b985a5f5e0815312d5e52b41263237af07b977e6bcbf3\n",
+            "Successfully built f5-tts transformers-stream-generator encodec\n",
+            "Installing collected packages: pydub, xxhash, websockets, uvicorn, tomlkit, semantic-version, ruff, python-multipart, pypinyin, markupsafe, jmespath, fsspec, filelock, ffmpy, dill, aiofiles, starlette, multiprocess, huggingface-hub, einx, botocore, s3transfer, gradio-client, fastapi, x-transformers, torchdiffeq, gradio, ema-pytorch, boto3, bitsandbytes, transformers-stream-generator, encodec, datasets, vocos, cached-path, f5-tts\n",
+            "  Attempting uninstall: markupsafe\n",
+            "    Found existing installation: MarkupSafe 3.0.2\n",
+            "    Uninstalling MarkupSafe-3.0.2:\n",
+            "      Successfully uninstalled MarkupSafe-3.0.2\n",
+            "  Attempting uninstall: fsspec\n",
+            "    Found existing installation: fsspec 2024.10.0\n",
+            "    Uninstalling fsspec-2024.10.0:\n",
+            "      Successfully uninstalled fsspec-2024.10.0\n",
+            "  Attempting uninstall: filelock\n",
+            "    Found existing installation: filelock 3.16.1\n",
+            "    Uninstalling filelock-3.16.1:\n",
+            "      Successfully uninstalled filelock-3.16.1\n",
+            "  Attempting uninstall: huggingface-hub\n",
+            "    Found existing installation: huggingface-hub 0.24.7\n",
+            "    Uninstalling huggingface-hub-0.24.7:\n",
+            "      Successfully uninstalled huggingface-hub-0.24.7\n",
+            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+            "gcsfs 2024.10.0 requires fsspec==2024.10.0, but you have fsspec 2024.9.0 which is incompatible.\n",
+            "pytensor 2.25.5 requires filelock>=3.15, but you have filelock 3.13.4 which is incompatible.\u001b[0m\u001b[31m\n",
+            "\u001b[0mSuccessfully installed aiofiles-23.2.1 bitsandbytes-0.44.1 boto3-1.35.54 botocore-1.35.54 cached-path-1.6.3 datasets-3.1.0 dill-0.3.8 einx-0.3.0 ema-pytorch-0.7.3 encodec-0.1.1 f5-tts-0.0.0 fastapi-0.115.4 ffmpy-0.4.0 filelock-3.13.4 fsspec-2024.9.0 gradio-4.44.1 gradio-client-1.3.0 huggingface-hub-0.23.5 jmespath-1.0.1 markupsafe-2.1.5 multiprocess-0.70.16 pydub-0.25.1 pypinyin-0.53.0 python-multipart-0.0.17 ruff-0.7.2 s3transfer-0.10.3 semantic-version-2.10.0 starlette-0.41.2 tomlkit-0.12.0 torchdiffeq-0.2.4 transformers-stream-generator-0.0.5 uvicorn-0.32.0 vocos-0.1.0 websockets-12.0 x-transformers-1.42.5 xxhash-3.5.0\n"
+          ]
+        }
+      ],
+      "source": [
+        "pip install git+https://github.com/jpgallegoar/Spanish-F5.git"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!f5-tts_infer-gradio"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "a2LYVge6IhOh",
+        "outputId": "be4d8d64-c020-4c97-eb57-ed0ceced7fba"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "2024-11-04 17:05:51.302161: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
+            "2024-11-04 17:05:51.328444: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
+            "2024-11-04 17:05:51.335942: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
+            "2024-11-04 17:05:51.354757: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
+            "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
+            "2024-11-04 17:05:52.875946: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
+            "Download Vocos from huggingface charactr/vocos-mel-24khz\n",
+            "config.yaml: 100% 461/461 [00:00<00:00, 2.61MB/s]\n",
+            "pytorch_model.bin: 100% 54.4M/54.4M [00:00<00:00, 139MB/s]\n",
+            "/usr/local/lib/python3.10/dist-packages/vocos/pretrained.py:70: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
+            "  state_dict = torch.load(model_path, map_location=\"cpu\")\n",
+            "model_1200000.safetensors: 100% 1.35G/1.35G [02:09<00:00, 10.4MB/s]\n",
+            "\n",
+            "vocab :  /usr/local/lib/python3.10/dist-packages/f5_tts/infer/examples/vocab.txt\n",
+            "tokenizer :  custom\n",
+            "model :  /root/.cache/huggingface/hub/models--jpgallegoar--F5-Spanish/snapshots/120ddcfa7813b928325a787b9ad2bf038d2c32df/model_1200000.safetensors \n",
+            "\n",
+            "Starting app...\n",
+            "Running on local URL:  http://127.0.0.1:7860\n",
+            "Running on public URL: https://dd1c9f211495273ff6.gradio.live\n",
+            "\n",
+            "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n",
+            "config.json: 100% 1.26k/1.26k [00:00<00:00, 1.89MB/s]\n",
+            "model.safetensors:  21% 336M/1.62G [00:32<02:03, 10.4MB/s]"
+          ]
+        }
+      ]
+    }
+  ]
+}

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