diff --git "a/notebooks/text_to_audio.ipynb" "b/notebooks/text_to_audio.ipynb"
new file mode 100644--- /dev/null
+++ "b/notebooks/text_to_audio.ipynb"
@@ -0,0 +1,209 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import os\n",
+ "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"1\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import sys\n",
+ "sys.path.append(\"../\")\n",
+ "\n",
+ "import torch\n",
+ "from auffusion_pipeline import AuffusionPipeline\n",
+ "from IPython.display import display, Audio"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "pretrained_model_name_or_path = \"auffusion/auffusion\"\n",
+ "dtype = torch.float16\n",
+ "device = \"cuda\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "The config attributes {'decay': 0.9999, 'inv_gamma': 1.0, 'min_decay': 0.0, 'optimization_step': 100000, 'power': 0.6666666666666666, 'update_after_step': 0, 'use_ema_warmup': False} were passed to UNet2DConditionModel, but are not expected and will be ignored. Please verify your config.json configuration file.\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Removing weight norm...\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "You are using a model of type clip_text_model to instantiate a model of type . This is not supported for all configurations of models and can yield errors.\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "LOADING CONDITION ENCODER 0\n",
+ "INITIATED: ConditionAdapter: {'text_encoder_name': 'text_encoder_0', 'condition_adapter_name': 'condition_adapter_0', 'condition_type': 'clip-vit-large-patch14_text', 'pretrained_model_name_or_path': 'openai/clip-vit-large-patch14', 'condition_max_length': 77, 'condition_dim': 768, 'cross_attention_dim': 768}\n",
+ "LOADED: ConditionAdapter from /home/xjl/Project/Audio/T2A/Auffusion/huggingface_checkpoint/auffusion/condition_adapter_0\n",
+ "LOADING CONDITION ADAPTER 0\n"
+ ]
+ }
+ ],
+ "source": [
+ "pipeline = AuffusionPipeline.from_pretrained(pretrained_model_name_or_path)\n",
+ "pipeline = pipeline.to(device, dtype)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "2696f2d9449c4d939760561121333b07",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ " 0%| | 0/50 [00:00\n",
+ " \n",
+ " Your browser does not support the audio element.\n",
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "prompt = \"Birds singing sweetly in a blooming garden\"\n",
+ "prompt = \"A kitten mewing for attention\"\n",
+ "\n",
+ "output = pipeline(prompt=prompt)\n",
+ "audio = output.audios[0]\n",
+ "display(Audio(audio, rate=16000))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "92ccaa24df8c4d138021301728a72ef8",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ " 0%| | 0/100 [00:00\n",
+ " \n",
+ " Your browser does not support the audio element.\n",
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "prompt = \"Birds singing sweetly in a blooming garden\"\n",
+ "prompt = \"A kitten mewing for attention\"\n",
+ "num_inference_steps = 100\n",
+ "guidance_scale = 7.5\n",
+ "seed = 42\n",
+ "\n",
+ "\n",
+ "generator = torch.Generator(device=device).manual_seed(seed)\n",
+ "\n",
+ "with torch.autocast(\"cuda\"):\n",
+ " output = pipeline(prompt=prompt, num_inference_steps=num_inference_steps, guidance_scale=guidance_scale, generator=generator) \n",
+ "\n",
+ "audio = output.audios[0]\n",
+ "display(Audio(audio, rate=16000))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "TTA",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.10.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}