From e787d0182f3651c23515b2afff5ce892f7197510 Mon Sep 17 00:00:00 2001 From: Lengyue Date: Sun, 5 May 2024 04:41:22 -0400 Subject: [PATCH] Use SFT medium as base model --- docs/en/finetune.md | 4 ++-- docs/en/inference.md | 8 +++---- docs/zh/finetune.md | 6 ++--- docs/zh/inference.md | 10 ++++---- .../configs/text2semantic_finetune.yaml | 2 +- fish_speech/webui/manage.py | 2 +- pyproject.toml | 1 - tools/api.py | 2 +- tools/llama/merge_lora.py | 2 +- tools/webui.py | 23 +------------------ 10 files changed, 19 insertions(+), 41 deletions(-) diff --git a/docs/en/finetune.md b/docs/en/finetune.md index fa72ccd0..694c39b2 100644 --- a/docs/en/finetune.md +++ b/docs/en/finetune.md @@ -148,7 +148,7 @@ After the command finishes executing, you should see the `quantized-dataset-ft.p Similarly, make sure you have downloaded the `LLAMA` weights. If not, run the following command: ```bash -huggingface-cli download fishaudio/fish-speech-1 text2semantic-sft-large-v1-4k.pth --local-dir checkpoints +huggingface-cli download fishaudio/fish-speech-1 text2semantic-sft-medium-v1-4k.pth --local-dir checkpoints ``` Finally, you can start the fine-tuning by running the following command: @@ -182,7 +182,7 @@ After training, you need to convert the LoRA weights to regular weights before p python tools/llama/merge_lora.py \ --llama-config dual_ar_2_codebook_large \ --lora-config r_8_alpha_16 \ - --llama-weight checkpoints/text2semantic-sft-large-v1-4k.pth \ + --llama-weight checkpoints/text2semantic-sft-medium-v1-4k.pth \ --lora-weight results/text2semantic-finetune-medium-lora/checkpoints/step_000000200.ckpt \ --output checkpoints/merged.ckpt ``` diff --git a/docs/en/inference.md b/docs/en/inference.md index bb050155..4befc16f 100644 --- a/docs/en/inference.md +++ b/docs/en/inference.md @@ -16,7 +16,7 @@ Download the required `vqgan` and `text2semantic` models from our Hugging Face r ```bash huggingface-cli download fishaudio/fish-speech-1 vq-gan-group-fsq-2x1024.pth --local-dir checkpoints -huggingface-cli download fishaudio/fish-speech-1 text2semantic-sft-large-v1-4k.pth --local-dir checkpoints +huggingface-cli download fishaudio/fish-speech-1 text2semantic-sft-medium-v1-4k.pth --local-dir checkpoints ``` ### 1. Generate prompt from voice: @@ -38,7 +38,7 @@ python tools/llama/generate.py \ --prompt-text "Your reference text" \ --prompt-tokens "fake.npy" \ --config-name dual_ar_2_codebook_large \ - --checkpoint-path "checkpoints/text2semantic-sft-large-v1-4k.pth" \ + --checkpoint-path "checkpoints/text2semantic-sft-medium-v1-4k.pth" \ --num-samples 2 \ --compile ``` @@ -69,7 +69,7 @@ We provide a HTTP API for inference. You can use the following command to start ```bash python -m tools.api \ --listen 0.0.0.0:8000 \ - --llama-checkpoint-path "checkpoints/text2semantic-sft-large-v1-4k.pth" \ + --llama-checkpoint-path "checkpoints/text2semantic-sft-medium-v1-4k.pth" \ --llama-config-name dual_ar_2_codebook_large \ --vqgan-checkpoint-path "checkpoints/vq-gan-group-fsq-2x1024.pth" ``` @@ -82,7 +82,7 @@ You can start the WebUI using the following command: ```bash python -m tools.webui \ - --llama-checkpoint-path "checkpoints/text2semantic-sft-large-v1-4k.pth" \ + --llama-checkpoint-path "checkpoints/text2semantic-sft-medium-v1-4k.pth" \ --llama-config-name dual_ar_2_codebook_large \ --vqgan-checkpoint-path "checkpoints/vq-gan-group-fsq-2x1024.pth" ``` diff --git a/docs/zh/finetune.md b/docs/zh/finetune.md index f01f4303..d4fde2f2 100644 --- a/docs/zh/finetune.md +++ b/docs/zh/finetune.md @@ -152,13 +152,13 @@ python tools/llama/build_dataset.py \ 同样的, 请确保你已经下载了 `LLAMA` 权重, 如果没有, 请运行以下命令: ```bash -huggingface-cli download fishaudio/fish-speech-1 text2semantic-sft-large-v1-4k.pth --local-dir checkpoints +huggingface-cli download fishaudio/fish-speech-1 text2semantic-sft-medium-v1-4k.pth --local-dir checkpoints ``` 对于中国大陆用户, 可使用 mirror 下载. ```bash -HF_ENDPOINT=https://hf-mirror.com huggingface-cli download fishaudio/fish-speech-1 text2semantic-sft-large-v1-4k.pth --local-dir checkpoints +HF_ENDPOINT=https://hf-mirror.com huggingface-cli download fishaudio/fish-speech-1 text2semantic-sft-medium-v1-4k.pth --local-dir checkpoints ``` 最后, 你可以运行以下命令来启动微调: @@ -192,7 +192,7 @@ python fish_speech/train.py --config-name text2semantic_finetune \ python tools/llama/merge_lora.py \ --llama-config dual_ar_2_codebook_large \ --lora-config r_8_alpha_16 \ - --llama-weight checkpoints/text2semantic-sft-large-v1-4k.pth \ + --llama-weight checkpoints/text2semantic-sft-medium-v1-4k.pth \ --lora-weight results/text2semantic-finetune-medium-lora/checkpoints/step_000000200.ckpt \ --output checkpoints/merged.ckpt ``` diff --git a/docs/zh/inference.md b/docs/zh/inference.md index 35a0ad89..232088c6 100644 --- a/docs/zh/inference.md +++ b/docs/zh/inference.md @@ -16,12 +16,12 @@ ```bash huggingface-cli download fishaudio/fish-speech-1 vq-gan-group-fsq-2x1024.pth --local-dir checkpoints -huggingface-cli download fishaudio/fish-speech-1 text2semantic-sft-large-v1-4k.pth --local-dir checkpoints +huggingface-cli download fishaudio/fish-speech-1 text2semantic-sft-medium-v1-4k.pth --local-dir checkpoints ``` 对于中国大陆用户，可使用mirror下载。 ```bash HF_ENDPOINT=https://hf-mirror.com huggingface-cli download fishaudio/fish-speech-1 vq-gan-group-fsq-2x1024.pth --local-dir checkpoints -HF_ENDPOINT=https://hf-mirror.com huggingface-cli download fishaudio/fish-speech-1 text2semantic-sft-large-v1-4k.pth --local-dir checkpoints +HF_ENDPOINT=https://hf-mirror.com huggingface-cli download fishaudio/fish-speech-1 text2semantic-sft-medium-v1-4k.pth --local-dir checkpoints ``` ### 1. 从语音生成 prompt: @@ -43,7 +43,7 @@ python tools/llama/generate.py \ --prompt-text "你的参考文本" \ --prompt-tokens "fake.npy" \ --config-name dual_ar_2_codebook_large \ - --checkpoint-path "checkpoints/text2semantic-sft-large-v1-4k.pth" \ + --checkpoint-path "checkpoints/text2semantic-sft-medium-v1-4k.pth" \ --num-samples 2 \ --compile ``` @@ -74,7 +74,7 @@ python tools/vqgan/inference.py \ ```bash python -m tools.api \ --listen 0.0.0.0:8000 \ - --llama-checkpoint-path "checkpoints/text2semantic-sft-large-v1-4k.pth" \ + --llama-checkpoint-path "checkpoints/text2semantic-sft-medium-v1-4k.pth" \ --llama-config-name dual_ar_2_codebook_large \ --vqgan-checkpoint-path "checkpoints/vq-gan-group-fsq-2x1024.pth" @@ -90,7 +90,7 @@ HF_ENDPOINT=https://hf-mirror.com python -m ... ```bash python -m tools.webui \ - --llama-checkpoint-path "checkpoints/text2semantic-sft-large-v1-4k.pth" \ + --llama-checkpoint-path "checkpoints/text2semantic-sft-medium-v1-4k.pth" \ --llama-config-name dual_ar_2_codebook_large \ --vqgan-checkpoint-path "checkpoints/vq-gan-group-fsq-2x1024.pth" ``` diff --git a/fish_speech/configs/text2semantic_finetune.yaml b/fish_speech/configs/text2semantic_finetune.yaml index 179df1b8..f347f58a 100644 --- a/fish_speech/configs/text2semantic_finetune.yaml +++ b/fish_speech/configs/text2semantic_finetune.yaml @@ -5,7 +5,7 @@ defaults: project: text2semantic_finetune_dual_ar max_length: 2048 -ckpt_path: checkpoints/text2semantic-sft-large-v1-4k.pth +ckpt_path: checkpoints/text2semantic-sft-medium-v1-4k.pth resume_weights_only: true # Lightning Trainer diff --git a/fish_speech/webui/manage.py b/fish_speech/webui/manage.py index 05523d66..8e25a7de 100644 --- a/fish_speech/webui/manage.py +++ b/fish_speech/webui/manage.py @@ -470,7 +470,7 @@ def generate_folder_name(): ckpt_path = ( "text2semantic-pretrain-medium-2k-v1.pth" if llama_base_config == "dual_ar_2_codebook_medium" - else "text2semantic-sft-large-v1-4k.pth" + else "text2semantic-sft-medium-v1-4k.pth" ) latest = list( diff --git a/pyproject.toml b/pyproject.toml index daca42dd..0989b3b5 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -34,7 +34,6 @@ dependencies = [ "vector_quantize_pytorch>=1.14.7", "samplerate>=0.2.1", "resampy>=0.4.3", - "spaces>=0.26.1", "einx[torch]==0.2.2" ] diff --git a/tools/api.py b/tools/api.py index 9fd619d5..13c817a1 100644 --- a/tools/api.py +++ b/tools/api.py @@ -225,7 +225,7 @@ def parse_args(): parser.add_argument( "--llama-checkpoint-path", type=str, - default="checkpoints/text2semantic-sft-large-v1-4k.pth", + default="checkpoints/text2semantic-sft-medium-v1-4k.pth", ) parser.add_argument( "--llama-config-name", type=str, default="dual_ar_2_codebook_large" diff --git a/tools/llama/merge_lora.py b/tools/llama/merge_lora.py index 89e60ece..d125d129 100644 --- a/tools/llama/merge_lora.py +++ b/tools/llama/merge_lora.py @@ -15,7 +15,7 @@ @click.option("--llama-config", type=str, default="dual_ar_2_codebook_large") @click.option("--lora-config", type=str, default="r_8_alpha_16") @click.option( - "--llama-weight", type=str, default="checkpoints/text2semantic-sft-large-v1-4k.pth" + "--llama-weight", type=str, default="checkpoints/text2semantic-sft-medium-v1-4k.pth" ) @click.option("--lora-weight", type=str, required=True) @click.option("--output", type=str, required=True) diff --git a/tools/webui.py b/tools/webui.py index 2c66a3e7..ee6fbb42 100644 --- a/tools/webui.py +++ b/tools/webui.py @@ -40,21 +40,6 @@ TEXTBOX_PLACEHOLDER = i18n("Put your text here.") SPACE_IMPORTED = False -try: - import spaces - - GPU_DECORATOR = spaces.GPU - SPACE_IMPORTED = True -except ImportError: - - def GPU_DECORATOR(func): - @wraps(func) - def wrapper(*args, **kwargs): - return func(*args, **kwargs) - - wrapper.original = func # ref - return wrapper - def build_html_error_message(error): return f""" @@ -65,7 +50,6 @@ def build_html_error_message(error): """ -@GPU_DECORATOR @torch.inference_mode() def inference( text, @@ -173,11 +157,6 @@ def inference( inference_stream = partial(inference, streaming=True) -if not SPACE_IMPORTED: - logger.info("‘spaces’ not imported, use original") - inference = inference.original - inference_stream = partial(inference, streaming=True) - def wav_chunk_header(sample_rate=44100, bit_depth=16, channels=1): buffer = io.BytesIO() @@ -343,7 +322,7 @@ def parse_args(): parser.add_argument( "--llama-checkpoint-path", type=Path, - default="checkpoints/text2semantic-sft-large-v1-4k.pth", + default="checkpoints/text2semantic-sft-medium-v1-4k.pth", ) parser.add_argument( "--llama-config-name", type=str, default="dual_ar_2_codebook_large"