diff --git a/README.md b/README.md
index b93d9dc..7e629d2 100644
--- a/README.md
+++ b/README.md
@@ -1,21 +1,28 @@
-# Retrieval-based-Voice-Conversion-WebUI
+<div align="center">
+
+<h1>Retrieval-based-Voice-Conversion-WebUI</h1>
+一个基于VITS的简单易用的语音转换（变声器）框架<br><br>
 
 [![madewithlove](https://forthebadge.com/images/badges/built-with-love.svg)](https://github.com/liujing04/Retrieval-based-Voice-Conversion-WebUI)
 
+<img src="https://counter.seku.su/cmoe?name=rvc&theme=r34" /><br>
+
 [![Open In Colab](https://img.shields.io/badge/Colab-F9AB00?style=for-the-badge&logo=googlecolab&color=525252)](https://colab.research.google.com/github/liujing04/Retrieval-based-Voice-Conversion-WebUI/blob/main/Retrieval_based_Voice_Conversion_WebUI.ipynb)
 [![Licence](https://img.shields.io/github/license/liujing04/Retrieval-based-Voice-Conversion-WebUI?style=for-the-badge)](https://github.com/liujing04/Retrieval-based-Voice-Conversion-WebUI/blob/main/%E4%BD%BF%E7%94%A8%E9%9C%80%E9%81%B5%E5%AE%88%E7%9A%84%E5%8D%8F%E8%AE%AE-LICENSE.txt)
 [![Huggingface](https://img.shields.io/badge/🤗%20-Spaces-blue.svg?style=for-the-badge)](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/)
 
-### 使用了RVC的实时语音转换 : [w-okada/voice-changer](https://github.com/w-okada/voice-changer)
-------
+</div>
 
-一个基于VITS的简单易用的语音转换（变声器）框架。
+------
 
 [**更新日志**](https://github.com/liujing04/Retrieval-based-Voice-Conversion-WebUI/blob/main/Changelog_CN.md)
 
 [**English**](./README_en.md) | [**中文简体**](./README.md)
 
 > 点此查看我们的[演示视频](https://www.bilibili.com/video/BV1pm4y1z7Gm/) !
+
+> 使用了RVC的实时语音转换: [w-okada/voice-changer](https://github.com/w-okada/voice-changer)
+
 ## 简介
 本仓库具有以下特点:
 + 使用top1特征模型检索来杜绝音色泄漏；
@@ -47,9 +54,13 @@ poetry install
 ```
 
 你也可以通过pip来安装依赖：
+
+**注意**: `MacOS`下`faiss 1.7.2`版本会导致抛出段错误，请将`requirements.txt`的对应条目改为`faiss-cpu==1.7.0`
+
 ```bash
 pip install -r requirements.txt
 ```
+
 ## 其他预模型准备
 RVC需要其他的一些预模型来推理和训练。
 
diff --git a/README_en.md b/README_en.md
index 6fe55e8..8e14e6b 100644
--- a/README_en.md
+++ b/README_en.md
@@ -40,9 +40,12 @@ poetry install
 ```
 You can also use pip to install the dependencies
 
+**Notice**: `faiss 1.7.2` will raise Segmentation Fault: 11 under `MacOS`, please change corresponding line in `requirements.txt` to `faiss-cpu==1.7.0`
+
 ```bash
 pip install -r requirements.txt
 ```
+
 ## Preparation of other Pre-models
 RVC requires other pre-models to infer and train.
 
diff --git a/README_v0.md b/README_v0.md
deleted file mode 100644
index 237679d..0000000
--- a/README_v0.md
+++ /dev/null
@@ -1,32 +0,0 @@
-# Retrieval-based-Voice-Conversion-WebUI
-
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/liujing04/Retrieval-based-Voice-Conversion-WebUI/blob/main/Retrieval_based_Voice_Conversion_WebUI.ipynb)
-
-缺失的2个文件夹和2个文件：
-
-hubert_base.pt
-
-ffmpeg（自己确保ffmpeg命令能执行就行）
-
-pretrained文件夹
-
-uvr5_weights文件夹
-
-文件太大github传不动，去huggingface上下https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main
-
-当然你也可以直接看看RVC-beta.7z这个文件→_→
-
-按照requirements.txt用pip装好环境，python infer-web.py就能用了
-
-根据经验，librosa numpy和numba三个包最好写死版本否则容易有坑，其他的包版本不太重要
-
-宣传视频：https://www.bilibili.com/video/BV1pm4y1z7Gm/
-
-教程见小白简易教程.doc
-
-We will develop an English version windows WebUI APP in 2 weeks.
-
-
-### Realtime Voice Conversion Software using RVC
-
-https://github.com/w-okada/voice-changer
diff --git a/Retrieval_based_Voice_Conversion_WebUI.ipynb b/Retrieval_based_Voice_Conversion_WebUI.ipynb
index eb549d8..a47f3b4 100644
--- a/Retrieval_based_Voice_Conversion_WebUI.ipynb
+++ b/Retrieval_based_Voice_Conversion_WebUI.ipynb
@@ -129,10 +129,10 @@
         "#@title 从谷歌云盘加载打包好的数据集到/content/dataset\n",
         "\n",
         "#@markdown 数据集位置\n",
-        "DATASET = \"/content/drive/MyDrive/dataset/lulucall_48k.zip\"  #@param {type:\"string\"}\n",
+        "DATASET = \"/content/drive/MyDrive/dataset/lulu20230327_32k.zip\"  #@param {type:\"string\"}\n",
         "\n",
         "!mkdir -p /content/dataset\n",
-        "!unzip -d /content/dataset {DATASET}"
+        "!unzip -d /content/dataset -B {DATASET}"
       ],
       "metadata": {
         "id": "Mwk7Q0Loqzjx"
@@ -140,13 +140,26 @@
       "execution_count": null,
       "outputs": []
     },
+    {
+      "cell_type": "code",
+      "source": [
+        "#@title 重命名数据集中的重名文件\n",
+        "!ls -a /content/dataset/\n",
+        "!rename 's/(\\w+)\\.(\\w+)~(\\d*)/$1_$3.$2/' /content/dataset/*.*~*"
+      ],
+      "metadata": {
+        "id": "PDlFxWHWEynD"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
     {
       "cell_type": "code",
       "source": [
         "#@title 启动web\n",
         "%cd /content/Retrieval-based-Voice-Conversion-WebUI\n",
-        "%load_ext tensorboard\n",
-        "%tensorboard --logdir /content/Retrieval-based-Voice-Conversion-WebUI/logs\n",
+        "# %load_ext tensorboard\n",
+        "# %tensorboard --logdir /content/Retrieval-based-Voice-Conversion-WebUI/logs\n",
         "!python3 infer-web.py --colab --pycmd python3"
       ],
       "metadata": {
@@ -164,7 +177,7 @@
         "#@markdown 模型名\n",
         "MODELNAME = \"lulu\"  #@param {type:\"string\"}\n",
         "#@markdown 模型epoch\n",
-        "MODELEPOCH = 7500  #@param {type:\"integer\"}\n",
+        "MODELEPOCH = 9600  #@param {type:\"integer\"}\n",
         "\n",
         "!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth /content/drive/MyDrive/{MODELNAME}_D_{MODELEPOCH}.pth\n",
         "!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth /content/drive/MyDrive/{MODELNAME}_G_{MODELEPOCH}.pth\n",
@@ -188,7 +201,7 @@
         "#@markdown 模型名\n",
         "MODELNAME = \"lulu\"  #@param {type:\"string\"}\n",
         "#@markdown 模型epoch\n",
-        "MODELEPOCH = 6000  #@param {type:\"integer\"}\n",
+        "MODELEPOCH = 7500  #@param {type:\"integer\"}\n",
         "\n",
         "!mkdir -p /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}\n",
         "\n",
@@ -241,7 +254,7 @@
         "#@markdown 模型名\n",
         "MODELNAME = \"lulu\"  #@param {type:\"string\"}\n",
         "#@markdown 停止的epoch\n",
-        "MODELEPOCH = 2500  #@param {type:\"integer\"}\n",
+        "MODELEPOCH = 3200  #@param {type:\"integer\"}\n",
         "#@markdown 保存epoch间隔\n",
         "EPOCHSAVE = 100  #@param {type:\"integer\"}\n",
         "#@markdown 采样率\n",
@@ -262,7 +275,7 @@
         "#@markdown 模型名\n",
         "MODELNAME = \"lulu\"  #@param {type:\"string\"}\n",
         "#@markdown 选中模型epoch\n",
-        "MODELEPOCH = 7700  #@param {type:\"integer\"}\n",
+        "MODELEPOCH = 9600  #@param {type:\"integer\"}\n",
         "\n",
         "!echo \"备份选中的模型。。。\"\n",
         "!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth /content/{MODELNAME}_D_{MODELEPOCH}.pth\n",
@@ -292,7 +305,7 @@
         "#@markdown 模型名\n",
         "MODELNAME = \"lulu\"  #@param {type:\"string\"}\n",
         "#@markdown 选中模型epoch\n",
-        "MODELEPOCH = 7700  #@param {type:\"integer\"}\n",
+        "MODELEPOCH = 9600  #@param {type:\"integer\"}\n",
         "\n",
         "!echo \"备份选中的模型。。。\"\n",
         "!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth /content/{MODELNAME}_D_{MODELEPOCH}.pth\n",
diff --git a/infer-web.py b/infer-web.py
index c838a2a..d2cd506 100644
--- a/infer-web.py
+++ b/infer-web.py
@@ -9,7 +9,7 @@ import faiss
 ncpu=cpu_count()
 ngpu=torch.cuda.device_count()
 gpu_infos=[]
-if(torch.cuda.is_available()==False or ngpu==0):if_gpu_ok=False
+if((not torch.cuda.is_available()) or ngpu==0):if_gpu_ok=False
 else:
     if_gpu_ok = False
     for i in range(ngpu):
@@ -79,7 +79,7 @@ def vc_single(sid,input_audio,f0_up_key,f0_file,f0_method,file_index,file_big_np
         if(hubert_model==None):load_hubert()
         if_f0 = cpt.get("f0", 1)
         audio_opt=vc.pipeline(hubert_model,net_g,sid,audio,times,f0_up_key,f0_method,file_index,file_big_npy,index_rate,if_f0,f0_file=f0_file)
-        print(times)
+        print("npy: ", times[0], "s, f0:", times[1], "s, infer: ", times[2], "s", sep='')
         return "Success", (tgt_sr, audio_opt)
     except:
         info=traceback.format_exc()
@@ -140,7 +140,7 @@ def uvr(model_name,inp_root,save_root_vocal,paths,save_root_ins):
         except:
             traceback.print_exc()
         print("clean_empty_cache")
-        torch.cuda.empty_cache()
+        if torch.cuda.is_available(): torch.cuda.empty_cache()
     yield "\n".join(infos)
 
 #一个选项卡全局只能有一个音色
@@ -152,7 +152,7 @@ def get_vc(sid):
             print("clean_empty_cache")
             del net_g, n_spk, vc, hubert_model,tgt_sr#,cpt
             hubert_model = net_g=n_spk=vc=hubert_model=tgt_sr=None
-            torch.cuda.empty_cache()
+            if torch.cuda.is_available(): torch.cuda.empty_cache()
             ###楼下不这么折腾清理不干净
             if_f0 = cpt.get("f0", 1)
             if (if_f0 == 1):
@@ -160,7 +160,7 @@ def get_vc(sid):
             else:
                 net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
             del net_g,cpt
-            torch.cuda.empty_cache()
+            if torch.cuda.is_available(): torch.cuda.empty_cache()
             cpt=None
         return {"visible": False, "__type__": "update"}
     person = "%s/%s" % (weight_root, sid)
diff --git a/infer/infer-pm-index256.py b/infer/infer-pm-index256.py
index dd94834..add0245 100644
--- a/infer/infer-pm-index256.py
+++ b/infer/infer-pm-index256.py
@@ -104,7 +104,7 @@ for idx,name in enumerate(["冬之花clip1.wav",]):##
         "padding_mask": padding_mask.to(device),
         "output_layer": 9,  # layer 9
     }
-    torch.cuda.synchronize()
+    if torch.cuda.is_available(): torch.cuda.synchronize()
     t0=ttime()
     with torch.no_grad():
         logits = model.extract_features(**inputs)
@@ -116,13 +116,13 @@ for idx,name in enumerate(["冬之花clip1.wav",]):##
     feats = torch.from_numpy(big_npy[I.squeeze()].astype("float16")).unsqueeze(0).to(device)
 
     feats=F.interpolate(feats.permute(0,2,1),scale_factor=2).permute(0,2,1)
-    torch.cuda.synchronize()
+    if torch.cuda.is_available(): torch.cuda.synchronize()
     t1=ttime()
     # p_len = min(feats.shape[1],10000,pitch.shape[0])#太大了爆显存
     p_len = min(feats.shape[1],10000)#
     pitch, pitchf = get_f0(audio, p_len,f0_up_key)
     p_len = min(feats.shape[1],10000,pitch.shape[0])#太大了爆显存
-    torch.cuda.synchronize()
+    if torch.cuda.is_available(): torch.cuda.synchronize()
     t2=ttime()
     feats = feats[:,:p_len, :]
     pitch = pitch[:p_len]
@@ -133,7 +133,7 @@ for idx,name in enumerate(["冬之花clip1.wav",]):##
     pitchf = torch.FloatTensor(pitchf).unsqueeze(0).to(device)
     with torch.no_grad():
         audio = net_g.infer(feats, p_len,pitch,pitchf,sid)[0][0, 0].data.cpu().float().numpy()#nsf
-    torch.cuda.synchronize()
+    if torch.cuda.is_available(): torch.cuda.synchronize()
     t3=ttime()
     ta0+=(t1-t0)
     ta1+=(t2-t1)
diff --git a/vc_infer_pipeline.py b/vc_infer_pipeline.py
index 30b03e3..e05ef4c 100644
--- a/vc_infer_pipeline.py
+++ b/vc_infer_pipeline.py
@@ -79,7 +79,7 @@ class VC(object):
         if(isinstance(index,type(None))==False and isinstance(big_npy,type(None))==False and index_rate!=0):
             npy = feats[0].cpu().numpy()
             if(self.is_half==True):npy=npy.astype("float32")
-            D, I = index.search(npy, 1)
+            _, I = index.search(npy, 1)
             npy=big_npy[I.squeeze()]
             if(self.is_half==True):npy=npy.astype("float16")
             feats = torch.from_numpy(npy).unsqueeze(0).to(self.device)*index_rate + (1-index_rate)*feats
@@ -99,7 +99,7 @@ class VC(object):
             else:
                 audio1 = (net_g.infer(feats, p_len, sid)[0][0, 0] * 32768).data.cpu().float().numpy().astype(np.int16)
         del feats,p_len,padding_mask
-        torch.cuda.empty_cache()
+        if torch.cuda.is_available(): torch.cuda.empty_cache()
         t2 = ttime()
         times[0] += (t1 - t0)
         times[2] += (t2 - t1)
@@ -160,5 +160,5 @@ class VC(object):
             audio_opt.append(self.vc(model,net_g,sid,audio_pad[t:],None,None,times,index,big_npy,index_rate)[self.t_pad_tgt:-self.t_pad_tgt])
         audio_opt=np.concatenate(audio_opt)
         del pitch,pitchf,sid
-        torch.cuda.empty_cache()
+        if torch.cuda.is_available(): torch.cuda.empty_cache()
         return audio_opt