diff --git a/recipes/ljspeech/fast_pitch_e2e/train_fast_pitch_e2e.py b/recipes/ljspeech/fast_pitch_e2e/train_fast_pitch_e2e.py
new file mode 100644
index 00000000..31b3da9c
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+++ b/recipes/ljspeech/fast_pitch_e2e/train_fast_pitch_e2e.py
@@ -0,0 +1,98 @@
+import os
+
+from trainer import Trainer, TrainerArgs
+
+from TTS.config.shared_configs import BaseAudioConfig, BaseDatasetConfig
+from TTS.tts.configs.fast_pitch_e2e_config import FastPitchE2EConfig
+from TTS.tts.datasets import load_tts_samples
+from TTS.tts.models.forward_tts_e2e import ForwardTTSE2E, ForwardTTSE2EArgs
+from TTS.tts.utils.text.tokenizer import TTSTokenizer
+from TTS.utils.audio import AudioProcessor
+
+output_path = os.path.dirname(os.path.abspath(__file__))
+
+# init configs
+dataset_config = BaseDatasetConfig(
+    name="ljspeech",
+    meta_file_train="metadata.csv",
+    # meta_file_attn_mask=os.path.join(output_path, "../LJSpeech-1.1/metadata_attn_mask.txt"),
+    path=os.path.join(output_path, "../LJSpeech-1.1/"),
+)
+
+audio_config = BaseAudioConfig(
+    sample_rate=22050,
+    do_trim_silence=True,
+    trim_db=60.0,
+    signal_norm=False,
+    mel_fmin=0.0,
+    mel_fmax=8000,
+    spec_gain=1.0,
+    log_func="np.log",
+    ref_level_db=20,
+    preemphasis=0.0,
+    num_mels=80,
+)
+
+# vocoder_config = HifiganConfig()
+model_args = ForwardTTSE2EArgs()
+
+config = FastPitchE2EConfig(
+    run_name="fast_pitch_e2e_ljspeech",
+    run_description="don't detach vocoder input.",
+    model_args=model_args,
+    audio=audio_config,
+    batch_size=32,
+    eval_batch_size=16,
+    num_loader_workers=8,
+    num_eval_loader_workers=4,
+    compute_input_seq_cache=True,
+    compute_f0=True,
+    f0_cache_path=os.path.join(output_path, "f0_cache"),
+    run_eval=True,
+    test_delay_epochs=-1,
+    epochs=1000,
+    text_cleaner="english_cleaners",
+    use_phonemes=True,
+    phoneme_language="en-us",
+    phoneme_cache_path=os.path.join(output_path, "phoneme_cache"),
+    precompute_num_workers=4,
+    print_step=50,
+    print_eval=False,
+    mixed_precision=False,
+    sort_by_audio_len=True,
+    output_path=output_path,
+    datasets=[dataset_config],
+    start_by_longest=False,
+    binary_align_loss_alpha=0.0
+)
+
+# INITIALIZE THE AUDIO PROCESSOR
+# Audio processor is used for feature extraction and audio I/O.
+# It mainly serves to the dataloader and the training loggers.
+ap = AudioProcessor.init_from_config(config)
+
+# INITIALIZE THE TOKENIZER
+# Tokenizer is used to convert text to sequences of token IDs.
+# If characters are not defined in the config, default characters are passed to the config
+tokenizer, config = TTSTokenizer.init_from_config(config)
+
+# LOAD DATA SAMPLES
+# Each sample is a list of ```[text, audio_file_path, speaker_name]```
+# You can define your custom sample loader returning the list of samples.
+# Or define your custom formatter and pass it to the `load_tts_samples`.
+# Check `TTS.tts.datasets.load_tts_samples` for more details.
+train_samples, eval_samples = load_tts_samples(
+    dataset_config,
+    eval_split=True,
+    eval_split_max_size=config.eval_split_max_size,
+    eval_split_size=config.eval_split_size,
+)
+
+# init the model
+model = ForwardTTSE2E(config, ap, tokenizer, speaker_manager=None)
+
+# init the trainer and 🚀
+trainer = Trainer(
+    TrainerArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
+)
+trainer.fit()