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Added Gradio app files correctly

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  1. LICENSE +21 -0
  2. README.md +98 -9
  3. Sesame_AI_CSM_Notebook.ipynb +854 -0
  4. csm-google-collab +1 -0
LICENSE ADDED
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+ MIT License
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+
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+ Copyright (c) 2025 Malhar Ujawane
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+
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+ Permission is hereby granted, free of charge, to any person obtaining a copy
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+ of this software and associated documentation files (the "Software"), to deal
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+ in the Software without restriction, including without limitation the rights
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+ to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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+ copies of the Software, and to permit persons to whom the Software is
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+ furnished to do so, subject to the following conditions:
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+
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+ The above copyright notice and this permission notice shall be included in all
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+ copies or substantial portions of the Software.
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+
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+ THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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+ IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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+ FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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+ AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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+ LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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+ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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+ SOFTWARE.
README.md CHANGED
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  ---
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- title: Sesame Aicsm
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- emoji: 🏢
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- colorFrom: indigo
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- colorTo: yellow
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- sdk: gradio
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- sdk_version: 5.22.0
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- app_file: app.py
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- pinned: false
 
 
 
 
 
 
 
 
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  ---
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- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ # 🧠 Sesame CSM-1B Google Colab Notebook
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+
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+ [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Justmalhar/csm-google-collab/blob/main/Sesame_AI_CSM_Notebook.ipynb)
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+
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+ > **Text-to-Speech Demo using Sesame's CSM-1B Model, Gradio UI, and HuggingFace Hub**
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+
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+ ---
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+
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+ ## 📌 Overview
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+
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+ This notebook demonstrates how to set up and run **Sesame's CSM-1B** Text-to-Speech model on **Google Colab** using Gradio for a browser-based UI.
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+
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+ - 🔊 Input: Text
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+ - 🎙️ Output: Realistic speech audio via pretrained TTS model
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+ - 🤖 Model: [`sesame/csm-1b`](https://www.google.com/search?q=site%3Ahuggingface.co+sesame%2Fcsm-1b)
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+
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+ ---
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+
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+ ## 🚀 Quick Start
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+
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+ ### 🔗 Run in Google Colab
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+ Click the badge above to launch the notebook directly in Google Colab.
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+
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+ ### 🧩 Steps to Execute
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+
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+ 1. **Install Gradio and dependencies**
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+ 2. **Clone the CSM repo** and install additional Python libraries via `requirements.txt`
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+ 3. **Authenticate** with HuggingFace using `notebook_login()`
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+ 4. **Load the model** using the helper from `generator.py`
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+ 5. **Launch Gradio** with either:
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+ - ✅ Simple `gr.Interface`
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+ - 💡 Full-featured `gr.Blocks` app
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+
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  ---
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+
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+ ## 🛠️ Requirements
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+
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+ > All dependencies are pre-installed in the notebook via `pip install`
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+
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+ Main libraries:
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+
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+ - `gradio`
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+ - `torch`, `torchaudio`
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+ - `transformers`
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+ - `huggingface_hub`
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+ - `moshi`
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+ - `torchtune`
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+ - `torchao`
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+ - `silentcipher` (from GitHub)
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+
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  ---
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+ ## 🧪 Model Source
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+
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+ - **Model**: [sesame/csm-1b](https://www.google.com/search?q=site%3Ahuggingface.co+sesame%2Fcsm-1b)
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+ - **Repository**: https://github.com/SesameAILabs/csm
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+ - **Audio Generation**: `generator.generate()` from cloned repo
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+
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+ ---
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+
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+ ## 🖼️ UI Modes
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+
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+ ### Simple Interface
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+
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+ ```python
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+ gr.Interface(
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+ fn=gradio_interface,
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+ inputs=[gr.Textbox(...), gr.Slider(...)],
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+ outputs=gr.Audio(...),
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+ title="Sesame CSM-1B Text-to-Speech"
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+ ).launch(share=True)
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+ ```
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+
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+ ### Advanced Blocks UI
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+
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+ - 🔤 Text Input + File Upload
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+ - 🎚️ Speaker Selector
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+ - 🎛️ Audio Controls (play, pause, stop)
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+ - 🔉 Volume Slider
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+ - 🔁 Event Binding via `.click()`
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+
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+ ---
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+
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+ ## 🧑‍💻 Author
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+
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+ - 👤 Malhar Ujawane
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+ - 🐦 [Twitter](https://x.com/justmalhar)
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+ - 💻 [GitHub](https://github.com/justmalhar)
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+
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+ ---
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+
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+ ## ⚠️ Notes
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+
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+ - Ensure your HuggingFace account has access to the model before logging in.
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+ - If you encounter `Model.__init__() missing required argument: 'config'`, verify model loading code inside `generator.py`.
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+
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+ ---
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+
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+ ## 🧬 License
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+
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+ MIT License (for the notebook). Model license terms apply as per [HuggingFace model card](https://huggingface.co/sesame/csm-1b).
Sesame_AI_CSM_Notebook.ipynb ADDED
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+ {
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+ "cells": [
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+ {
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+ "cell_type": "markdown",
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+ "metadata": {
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+ "colab_type": "text",
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+ "id": "view-in-github"
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+ },
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+ "source": [
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+ "<a href=\"https://colab.research.google.com/github/Justmalhar/csm-google-collab/blob/main/Sesame_AI_CSM_Notebook.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "metadata": {
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+ "id": "Ww36-N-bgcnA"
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+ },
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+ "source": [
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+ "# Sesame AI - Google Collab CSM notebook\n",
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+ "\n",
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+ "Author: justmalhar\n",
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+ "\n",
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+ "http://x.com/justmalhar\n",
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+ "\n",
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+ "http://github.com/justmalhar\n",
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+ "\n",
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+ "HuggingFace Model - https://huggingface.co/sesame/csm-1b\n",
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+ "\n",
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+ "## Instructions\n",
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+ "\n",
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+ "Run each step below till you see the Gradio UI running\n",
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+ "\n",
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+ "\n",
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+ "## Steps:\n",
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+ "1. Setup Gradio\n",
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+ "2. Clone the repo and install the requirments\n",
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+ "3. Login with HuggingFace account to access the model\n",
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+ "4. Run all steps till you see the Gradio UI"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 1,
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+ "metadata": {
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+ "colab": {
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+ "base_uri": "https://localhost:8080/"
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+ },
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+ "id": "T6S72oH6hTd5",
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+ "outputId": "cd15a8fb-2033-49a5-8243-96ca208a7385"
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+ },
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+ "outputs": [
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+ {
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+ "name": "stdout",
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+ "output_type": "stream",
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+ "text": [
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+ "Collecting torch\n",
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+ " Downloading torch-2.6.0-cp312-cp312-win_amd64.whl.metadata (28 kB)\n",
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+ "Downloading safehttpx-0.1.6-py3-none-any.whl (8.7 kB)\n",
539
+ "Using cached safetensors-0.5.3-cp38-abi3-win_amd64.whl (308 kB)\n",
540
+ "Downloading semantic_version-2.10.0-py2.py3-none-any.whl (15 kB)\n",
541
+ "Downloading starlette-0.46.1-py3-none-any.whl (71 kB)\n",
542
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+ "Downloading tomlkit-0.13.2-py3-none-any.whl (37 kB)\n",
549
+ "Downloading typer-0.15.2-py3-none-any.whl (45 kB)\n",
550
+ "Using cached typing_extensions-4.12.2-py3-none-any.whl (37 kB)\n",
551
+ "Downloading uvicorn-0.34.0-py3-none-any.whl (62 kB)\n",
552
+ "Downloading ffmpy-0.5.0-py3-none-any.whl (6.0 kB)\n",
553
+ "Using cached filelock-3.18.0-py3-none-any.whl (16 kB)\n",
554
+ "Using cached networkx-3.4.2-py3-none-any.whl (1.7 MB)\n",
555
+ "Using cached pydub-0.25.1-py2.py3-none-any.whl (32 kB)\n",
556
+ "Downloading annotated_types-0.7.0-py3-none-any.whl (13 kB)\n",
557
+ "Using cached mpmath-1.3.0-py3-none-any.whl (536 kB)\n",
558
+ "Downloading shellingham-1.5.4-py2.py3-none-any.whl (9.8 kB)\n",
559
+ "Installing collected packages: pydub, mpmath, typing-extensions, tomlkit, sympy, shellingham, semantic-version, safetensors, ruff, python-multipart, orjson, networkx, groovy, fsspec, filelock, ffmpy, annotated-types, aiofiles, uvicorn, torch, starlette, pydantic-core, huggingface_hub, typer, torchaudio, tokenizers, safehttpx, pydantic, gradio-client, transformers, fastapi, gradio\n",
560
+ " Attempting uninstall: typing-extensions\n",
561
+ " Found existing installation: typing_extensions 4.10.0\n",
562
+ " Uninstalling typing_extensions-4.10.0:\n",
563
+ " Successfully uninstalled typing_extensions-4.10.0\n",
564
+ "Successfully installed aiofiles-23.2.1 annotated-types-0.7.0 fastapi-0.115.11 ffmpy-0.5.0 filelock-3.18.0 fsspec-2025.3.0 gradio-5.22.0 gradio-client-1.8.0 groovy-0.1.2 huggingface_hub-0.29.3 mpmath-1.3.0 networkx-3.4.2 orjson-3.10.15 pydantic-2.10.6 pydantic-core-2.27.2 pydub-0.25.1 python-multipart-0.0.20 ruff-0.11.2 safehttpx-0.1.6 safetensors-0.5.3 semantic-version-2.10.0 shellingham-1.5.4 starlette-0.46.1 sympy-1.13.1 tokenizers-0.21.1 tomlkit-0.13.2 torch-2.6.0 torchaudio-2.6.0 transformers-4.50.0 typer-0.15.2 typing-extensions-4.12.2 uvicorn-0.34.0\n"
565
+ ]
566
+ }
567
+ ],
568
+ "source": [
569
+ "# Reinstall required dependencies\n",
570
+ "!pip install torch torchaudio transformers huggingface_hub gradio"
571
+ ]
572
+ },
573
+ {
574
+ "cell_type": "markdown",
575
+ "metadata": {
576
+ "id": "ssphqLJugbrI"
577
+ },
578
+ "source": []
579
+ },
580
+ {
581
+ "cell_type": "code",
582
+ "execution_count": 2,
583
+ "metadata": {
584
+ "colab": {
585
+ "base_uri": "https://localhost:8080/"
586
+ },
587
+ "collapsed": true,
588
+ "id": "ObK_fhW7iCAn",
589
+ "outputId": "a483389f-82f3-4d07-e1b5-6cc4c73bae21"
590
+ },
591
+ "outputs": [
592
+ {
593
+ "name": "stdout",
594
+ "output_type": "stream",
595
+ "text": [
596
+ "c:\\Users\\PALLAVI\\csm-google-collab\\csm-google-collab\n"
597
+ ]
598
+ },
599
+ {
600
+ "name": "stderr",
601
+ "output_type": "stream",
602
+ "text": [
603
+ "Cloning into 'csm-google-collab'...\n",
604
+ "c:\\Users\\PALLAVI\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\IPython\\core\\magics\\osm.py:417: UserWarning: using dhist requires you to install the `pickleshare` library.\n",
605
+ " self.shell.db['dhist'] = compress_dhist(dhist)[-100:]\n"
606
+ ]
607
+ }
608
+ ],
609
+ "source": [
610
+ "# Clone the Sesame CSM repository\n",
611
+ "!git clone https://github.com/Justmalhar/csm-google-collab.git\n",
612
+ "%cd csm-google-collab"
613
+ ]
614
+ },
615
+ {
616
+ "cell_type": "code",
617
+ "execution_count": 3,
618
+ "metadata": {
619
+ "colab": {
620
+ "base_uri": "https://localhost:8080/"
621
+ },
622
+ "collapsed": true,
623
+ "id": "cr1XnB10Zf4z",
624
+ "outputId": "d5d175fe-6c10-4b6d-9ffb-d40b29adcd04"
625
+ },
626
+ "outputs": [
627
+ {
628
+ "name": "stderr",
629
+ "output_type": "stream",
630
+ "text": [
631
+ "ERROR: Could not open requirements file: [Errno 2] No such file or directory: '/content/csm/requirements.txt'\n"
632
+ ]
633
+ }
634
+ ],
635
+ "source": [
636
+ "# Install dependencies from requirements.txt\n",
637
+ "!pip install -r /content/csm/requirements.txt"
638
+ ]
639
+ },
640
+ {
641
+ "cell_type": "code",
642
+ "execution_count": 4,
643
+ "metadata": {
644
+ "id": "YV8hf1Y7iEl0"
645
+ },
646
+ "outputs": [],
647
+ "source": [
648
+ "#Add the repository to Python's path\n",
649
+ "import sys\n",
650
+ "sys.path.append(\"/content/csm\")"
651
+ ]
652
+ },
653
+ {
654
+ "cell_type": "code",
655
+ "execution_count": 5,
656
+ "metadata": {
657
+ "collapsed": true,
658
+ "id": "8AvFx6f4iMSW"
659
+ },
660
+ "outputs": [
661
+ {
662
+ "name": "stderr",
663
+ "output_type": "stream",
664
+ "text": [
665
+ "c:\\Users\\PALLAVI\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\huggingface_hub\\utils\\_deprecation.py:38: FutureWarning: Deprecated positional argument(s) used in 'notebook_login': pass new_session='' as keyword args. From version 1.0 passing these as positional arguments will result in an error,\n",
666
+ " warnings.warn(\n"
667
+ ]
668
+ }
669
+ ],
670
+ "source": [
671
+ "# Authenticate with Hugging Face\n",
672
+ "from huggingface_hub import notebook_login\n",
673
+ "notebook_login(\"\")"
674
+ ]
675
+ },
676
+ {
677
+ "cell_type": "code",
678
+ "execution_count": null,
679
+ "metadata": {
680
+ "colab": {
681
+ "base_uri": "https://localhost:8080/",
682
+ "height": 356
683
+ },
684
+ "collapsed": true,
685
+ "id": "3CsTqgqZiUls",
686
+ "outputId": "8966902a-5d4d-4ba4-f8f7-12e6830cf676"
687
+ },
688
+ "outputs": [
689
+ {
690
+ "ename": "OSError",
691
+ "evalue": "sesame/csm-1b does not appear to have a file named pytorch_model.bin, model.safetensors, tf_model.h5, model.ckpt or flax_model.msgpack.",
692
+ "output_type": "error",
693
+ "traceback": [
694
+ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
695
+ "\u001b[1;31mOSError\u001b[0m Traceback (most recent call last)",
696
+ "Cell \u001b[1;32mIn[8], line 9\u001b[0m\n\u001b[0;32m 6\u001b[0m config \u001b[38;5;241m=\u001b[39m AutoConfig\u001b[38;5;241m.\u001b[39mfrom_pretrained(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msesame/csm-1b\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m 8\u001b[0m \u001b[38;5;66;03m# Load the model with the configuration\u001b[39;00m\n\u001b[1;32m----> 9\u001b[0m model \u001b[38;5;241m=\u001b[39m \u001b[43mAutoModel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_pretrained\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43msesame/csm-1b\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconfig\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 10\u001b[0m model\u001b[38;5;241m.\u001b[39mto(device\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcuda\u001b[39m\u001b[38;5;124m\"\u001b[39m, dtype\u001b[38;5;241m=\u001b[39mtorch\u001b[38;5;241m.\u001b[39mbfloat16)\n\u001b[0;32m 11\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mModel loaded successfully! 🎉\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
697
+ "File \u001b[1;32mc:\\Users\\PALLAVI\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\transformers\\models\\auto\\auto_factory.py:573\u001b[0m, in \u001b[0;36m_BaseAutoModelClass.from_pretrained\u001b[1;34m(cls, pretrained_model_name_or_path, *model_args, **kwargs)\u001b[0m\n\u001b[0;32m 571\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mtype\u001b[39m(config) \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_model_mapping\u001b[38;5;241m.\u001b[39mkeys():\n\u001b[0;32m 572\u001b[0m model_class \u001b[38;5;241m=\u001b[39m _get_model_class(config, \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_model_mapping)\n\u001b[1;32m--> 573\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mmodel_class\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_pretrained\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 574\u001b[0m \u001b[43m \u001b[49m\u001b[43mpretrained_model_name_or_path\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mmodel_args\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconfig\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[43mhub_kwargs\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\n\u001b[0;32m 575\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 576\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[0;32m 577\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUnrecognized configuration class \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mconfig\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m for this kind of AutoModel: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 578\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mModel type should be one of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(c\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mfor\u001b[39;00m\u001b[38;5;250m \u001b[39mc\u001b[38;5;250m \u001b[39m\u001b[38;5;129;01min\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_model_mapping\u001b[38;5;241m.\u001b[39mkeys())\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 579\u001b[0m )\n",
698
+ "File \u001b[1;32mc:\\Users\\PALLAVI\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\transformers\\modeling_utils.py:272\u001b[0m, in \u001b[0;36mrestore_default_torch_dtype.<locals>._wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 270\u001b[0m old_dtype \u001b[38;5;241m=\u001b[39m torch\u001b[38;5;241m.\u001b[39mget_default_dtype()\n\u001b[0;32m 271\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m--> 272\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\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\u001b[0;32m 273\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[0;32m 274\u001b[0m torch\u001b[38;5;241m.\u001b[39mset_default_dtype(old_dtype)\n",
699
+ "File \u001b[1;32mc:\\Users\\PALLAVI\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\transformers\\modeling_utils.py:4317\u001b[0m, in \u001b[0;36mPreTrainedModel.from_pretrained\u001b[1;34m(cls, pretrained_model_name_or_path, config, cache_dir, ignore_mismatched_sizes, force_download, local_files_only, token, revision, use_safetensors, weights_only, *model_args, **kwargs)\u001b[0m\n\u001b[0;32m 4312\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m gguf_file \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m hf_quantizer \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\u001b[0;32m 4313\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[0;32m 4314\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mYou cannot combine Quantization and loading a model from a GGUF file, try again by making sure you did not passed a `quantization_config` or that you did not load a quantized model from the Hub.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 4315\u001b[0m )\n\u001b[1;32m-> 4317\u001b[0m checkpoint_files, sharded_metadata \u001b[38;5;241m=\u001b[39m \u001b[43m_get_resolved_checkpoint_files\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 4318\u001b[0m \u001b[43m \u001b[49m\u001b[43mpretrained_model_name_or_path\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpretrained_model_name_or_path\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 4319\u001b[0m \u001b[43m \u001b[49m\u001b[43msubfolder\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msubfolder\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 4320\u001b[0m \u001b[43m \u001b[49m\u001b[43mvariant\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mvariant\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 4321\u001b[0m \u001b[43m \u001b[49m\u001b[43mgguf_file\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mgguf_file\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 4322\u001b[0m \u001b[43m \u001b[49m\u001b[43mfrom_tf\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfrom_tf\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 4323\u001b[0m \u001b[43m \u001b[49m\u001b[43mfrom_flax\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfrom_flax\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 4324\u001b[0m \u001b[43m \u001b[49m\u001b[43muse_safetensors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43muse_safetensors\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 4325\u001b[0m \u001b[43m \u001b[49m\u001b[43mcache_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcache_dir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 4326\u001b[0m \u001b[43m \u001b[49m\u001b[43mforce_download\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mforce_download\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 4327\u001b[0m \u001b[43m \u001b[49m\u001b[43mproxies\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mproxies\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 4328\u001b[0m \u001b[43m \u001b[49m\u001b[43mlocal_files_only\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlocal_files_only\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 4329\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 4330\u001b[0m \u001b[43m \u001b[49m\u001b[43muser_agent\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43muser_agent\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 4331\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 4332\u001b[0m \u001b[43m \u001b[49m\u001b[43mcommit_hash\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcommit_hash\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 4333\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 4335\u001b[0m is_sharded \u001b[38;5;241m=\u001b[39m sharded_metadata \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\u001b[0;32m 4336\u001b[0m is_quantized \u001b[38;5;241m=\u001b[39m hf_quantizer \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",
700
+ "File \u001b[1;32mc:\\Users\\PALLAVI\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\transformers\\modeling_utils.py:1130\u001b[0m, in \u001b[0;36m_get_resolved_checkpoint_files\u001b[1;34m(pretrained_model_name_or_path, subfolder, variant, gguf_file, from_tf, from_flax, use_safetensors, cache_dir, force_download, proxies, local_files_only, token, user_agent, revision, commit_hash)\u001b[0m\n\u001b[0;32m 1124\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mEnvironmentError\u001b[39;00m(\n\u001b[0;32m 1125\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mpretrained_model_name_or_path\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m does not appear to have a file named\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 1126\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m_add_variant(WEIGHTS_NAME,\u001b[38;5;250m \u001b[39mvariant)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m but there is a file without the variant\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 1127\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mvariant\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m. Use `variant=None` to load this model from those weights.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 1128\u001b[0m )\n\u001b[0;32m 1129\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m-> 1130\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mEnvironmentError\u001b[39;00m(\n\u001b[0;32m 1131\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mpretrained_model_name_or_path\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m does not appear to have a file named\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 1132\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m_add_variant(WEIGHTS_NAME,\u001b[38;5;250m \u001b[39mvariant)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m, \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m_add_variant(SAFE_WEIGHTS_NAME,\u001b[38;5;250m \u001b[39mvariant)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m,\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 1133\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mTF2_WEIGHTS_NAME\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m, \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mTF_WEIGHTS_NAME\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m or \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mFLAX_WEIGHTS_NAME\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 1134\u001b[0m )\n\u001b[0;32m 1136\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mEnvironmentError\u001b[39;00m:\n\u001b[0;32m 1137\u001b[0m \u001b[38;5;66;03m# Raise any environment error raise by `cached_file`. It will have a helpful error message adapted\u001b[39;00m\n\u001b[0;32m 1138\u001b[0m \u001b[38;5;66;03m# to the original exception.\u001b[39;00m\n\u001b[0;32m 1139\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m\n",
701
+ "\u001b[1;31mOSError\u001b[0m: sesame/csm-1b does not appear to have a file named pytorch_model.bin, model.safetensors, tf_model.h5, model.ckpt or flax_model.msgpack."
702
+ ]
703
+ }
704
+ ],
705
+ "source": [
706
+ "# Load the Model\n",
707
+ "from transformers import AutoModel, AutoConfig\n",
708
+ "import torch\n",
709
+ "\n",
710
+ "# Load the configuration\n",
711
+ "config = AutoConfig.from_pretrained(\"sesame/csm-1b\")\n",
712
+ "\n",
713
+ "# Load the model with the configuration\n",
714
+ "model = AutoModel.from_pretrained(\"sesame/csm-1b\", config=config)\n",
715
+ "model.to(device=\"cuda\", dtype=torch.bfloat16)\n",
716
+ "print(\"Model loaded successfully!\")"
717
+ ]
718
+ },
719
+ {
720
+ "cell_type": "code",
721
+ "execution_count": null,
722
+ "metadata": {
723
+ "id": "mdpfkA6qiZaZ"
724
+ },
725
+ "outputs": [],
726
+ "source": [
727
+ "# Define the generate_audio function (replace with your actual implementation)\n",
728
+ "def generate_audio(text, speaker_id):\n",
729
+ " \"\"\"\n",
730
+ " Placeholder function for generating audio from text.\n",
731
+ " Replace this with your actual implementation.\n",
732
+ " \"\"\"\n",
733
+ " # Simulate audio generation\n",
734
+ " print(f\"Generating audio for text: {text} with speaker ID: {speaker_id}\")\n",
735
+ " # Return a placeholder audio file path\n",
736
+ " return \"/content/dummy_audio.wav\"\n"
737
+ ]
738
+ },
739
+ {
740
+ "cell_type": "code",
741
+ "execution_count": null,
742
+ "metadata": {
743
+ "id": "Whv2TT-CdFBq"
744
+ },
745
+ "outputs": [],
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+ "source": [
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+ "# Define the Gradio interface using Blocks API\n",
748
+ "import gradio as gr\n",
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+ "\n",
750
+ "with gr.Blocks(title=\"Sesame CSM-1B Text-to-Speech\") as demo:\n",
751
+ " gr.Markdown(\"# 🎙️ Sesame CSM-1B Text-to-Speech\")\n",
752
+ " gr.Markdown(\"Generate high-quality audio from text using the Sesame CSM-1B model.\")\n",
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+ "\n",
754
+ " with gr.Row():\n",
755
+ " with gr.Column():\n",
756
+ " # Text input\n",
757
+ " text_input = gr.Textbox(label=\"Enter Text\", placeholder=\"Type your text here...\", lines=5)\n",
758
+ "\n",
759
+ " # Speaker selection\n",
760
+ " speaker_dropdown = gr.Dropdown(\n",
761
+ " choices=[\"Speaker 0\", \"Speaker 1\", \"Speaker 2\", \"Speaker 3\"], # Add more options if needed\n",
762
+ " label=\"Select Speaker\",\n",
763
+ " value=\"Speaker 0\"\n",
764
+ " )\n",
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+ "\n",
766
+ " # File upload for text\n",
767
+ " file_upload = gr.File(label=\"Or Upload a Text File\", file_types=[\".txt\"])\n",
768
+ "\n",
769
+ " # Generate and Cancel buttons\n",
770
+ " with gr.Row():\n",
771
+ " generate_button = gr.Button(\"Generate Audio 🎵\")\n",
772
+ " cancel_button = gr.Button(\"Cancel ❌\")\n",
773
+ "\n",
774
+ " with gr.Column():\n",
775
+ " # Audio output\n",
776
+ " audio_output = gr.Audio(label=\"Generated Audio\", interactive=False)\n",
777
+ "\n",
778
+ " # Playback controls\n",
779
+ " with gr.Row():\n",
780
+ " play_button = gr.Button(\"▶️ Play\")\n",
781
+ " pause_button = gr.Button(\"⏸️ Pause\")\n",
782
+ " stop_button = gr.Button(\"⏹️ Stop\")\n",
783
+ "\n",
784
+ " # Volume control\n",
785
+ " volume_slider = gr.Slider(minimum=0, maximum=100, value=50, label=\"Volume\")\n",
786
+ "\n",
787
+ " # Define interactions\n",
788
+ " def process_input(text, file, speaker, cancel_flag):\n",
789
+ " if cancel_flag:\n",
790
+ " return \"Process canceled by user.\"\n",
791
+ "\n",
792
+ " if file is not None:\n",
793
+ " # Read text from the uploaded file\n",
794
+ " with open(file.name, \"r\") as f:\n",
795
+ " text = f.read()\n",
796
+ "\n",
797
+ " # Get speaker ID from the dropdown\n",
798
+ " speaker_id = int(speaker.split()[-1])\n",
799
+ "\n",
800
+ " # Generate audio\n",
801
+ " audio_file = generate_audio(text, speaker_id)\n",
802
+ " return audio_file\n",
803
+ "\n",
804
+ " # Link inputs and outputs\n",
805
+ " generate_button.click(\n",
806
+ " fn=process_input,\n",
807
+ " inputs=[text_input, file_upload, speaker_dropdown, cancel_button],\n",
808
+ " outputs=audio_output\n",
809
+ " )\n",
810
+ "\n",
811
+ " # Cancel button logic\n",
812
+ " cancel_button.click(\n",
813
+ " fn=lambda: \"Process canceled by user.\",\n",
814
+ " inputs=None,\n",
815
+ " outputs=audio_output\n",
816
+ " )\n",
817
+ "\n",
818
+ " # Playback controls (placeholders, as Gradio Audio already has built-in controls)\n",
819
+ " play_button.click(fn=lambda: None)\n",
820
+ " pause_button.click(fn=lambda: None)\n",
821
+ " stop_button.click(fn=lambda: None)\n",
822
+ "\n",
823
+ "# Launch the Gradio app\n",
824
+ "demo.launch(share=True) # Set `share=True` to get a public link"
825
+ ]
826
+ }
827
+ ],
828
+ "metadata": {
829
+ "accelerator": "GPU",
830
+ "colab": {
831
+ "gpuType": "T4",
832
+ "include_colab_link": true,
833
+ "provenance": []
834
+ },
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+ "kernelspec": {
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+ "display_name": "Python 3",
837
+ "name": "python3"
838
+ },
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+ "language_info": {
840
+ "codemirror_mode": {
841
+ "name": "ipython",
842
+ "version": 3
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+ },
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+ "file_extension": ".py",
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+ "mimetype": "text/x-python",
846
+ "name": "python",
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+ "nbconvert_exporter": "python",
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+ "pygments_lexer": "ipython3",
849
+ "version": "3.12.6"
850
+ }
851
+ },
852
+ "nbformat": 4,
853
+ "nbformat_minor": 0
854
+ }
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+ Subproject commit 3b40a8aa6b18f3b77eaae597913f7a6522b95251