Issue with Using pyannote/speaker-diarization Gated Model in Colab and API

Beginners
1

Hi everyone,

I’m currently working on my engineering thesis, which involves analyzing speaker diarization for Polish audio files. I’m trying to use the pyannote/speaker-diarization model to perform this task, but I’ve encountered several issues that I haven’t been able to resolve, even after trying various approaches. Here’s a summary of my problem:

  1. Access Granted but Model Not Running:
  • I’ve been granted access to the gated model on Hugging Face. However, when I try to use the model through the Inference API widget on the model’s page, I receive the error: “The API does not support running gated models for community models with framework: pyannote-audio.”
  1. Attempt with Google Colab:
  • I tried running the model locally using Google Colab and pyannote.audio. Despite authenticating successfully with my Hugging Face token, I encountered the following error: “AttributeError: ‘NoneType’ object has no attribute ‘eval’.”
  1. Context of My Work:
  • As part of my thesis, I need to analyze audio files and identify the number of speakers present. I have limited time to complete this, and I’m unsure how to proceed given these obstacles.

Could you please guide me on:

  • How to properly use the model via the Inference API or another simple method.
  • Resolving the issues I’m encountering in Colab.
  • Any alternative approaches for speaker diarization with Hugging Face models.

I would greatly appreciate any help or suggestions, as this is a critical part of my thesis, and I’m running out of time.

Thank you in advance!

Best regards,
Ola

1 Like
2

技術挑戰是一場學習之旅

在使用 pyannote 的 Speaker Diarization 模型時，遇到挑戰是非常正常的事情，就像學習任何新技能一樣。第一次騎自行車時，我們可能會摔倒，但隨著經驗的積累，我們逐漸找到平衡，最終能自由馳騁。

When working with the pyannote Speaker Diarization model, facing challenges is a completely normal part of the learning process. It’s much like picking up any new skill – your first bike ride might end in a fall, but with practice, you’ll find balance and ride freely.

步驟 1：檢查 API Token（開啟大門的鑰匙）

模型執行的第一步，是確保您擁有 Hugging Face 的 API Token。這可以被看作是一把通往模型功能世界的「鑰匙」。如果沒有這把鑰匙，我們無法順利進入這個領域。

Step 1: Check Your API Token (“The Key to Unlock the Door”)

The first step to running the model is ensuring you have a valid Hugging Face API Token. This token acts as your “key” to accessing the model’s functionality. Without it, the door to this powerful tool remains closed.

如何獲取 API Token：

  1. 登錄您的 Hugging Face 賬戶。

  2. 點擊右上角頭像，選擇「Settings」。

  3. 進入「Access Tokens」，生成並複製您的 API Token。

  4. 在 Google Colab 中使用以下代碼完成登錄：

from huggingface_hub import login

login(token=”YOUR_API_TOKEN“)

How to retrieve your API Token:

  1. Log in to your Hugging Face account.

  2. Click on your profile icon and select “Settings.”

  3. Navigate to “Access Tokens,” generate a new token, and copy it.

  4. Use the following code in Google Colab to log in:

from huggingface_hub import login

login(token=”YOUR_API_TOKEN“)

步驟 2：確認模型訪問權限

即使擁有了「鑰匙」，我們還需要確保模型的大門是否對我們敞開。某些模型（例如 pyannote/speaker-diarization）需要特別的訪問權限才能使用。

Step 2: Verify Model Access Permissions

Even with the “key,” it’s essential to confirm that the model’s “door” is open to you. Some models, like pyannote/speaker-diarization, require specific access permissions.

確認步驟：

  1. 在 Hugging Face 平台找到目標模型。

  2. 查看是否需要申請訪問權限。

  3. 如果需要，提交訪問申請並等待批准。

Steps to Verify:

  1. Locate the target model on the Hugging Face platform.

  2. Check if access permissions need to be requested.

  3. If required, submit a request and wait for approval.

步驟 3：檢查執行環境設置

如果以上步驟都已完成，但仍出現問題，請檢查您的執行環境是否正確配置。例如：

• 確保 Colab 中已安裝 pyannote.audio 及其所有依賴項。

• 使用以下命令進行安裝：

pip install pyannote.audio

Step 3: Check Your Runtime Environment

If the above steps are complete but issues persist, verify that your runtime environment is properly configured. For instance:

• Ensure pyannote.audio and its dependencies are installed in Colab.

• Use the following command to install:

pip install pyannote.audio

面對挑戰是進步的契機

希望這些建議能幫助您解決目前的問題！如果您仍然遇到困難，請隨時補充更多細節，我們可以一起探索更好的解決方案。技術挑戰的過程，雖然可能伴隨著挫折，但正是它讓我們成長並更加了解 AI 的強大潛力。

I hope these suggestions help you resolve your issues! If you still face difficulties, feel free to share more details so we can explore better solutions together. While technical challenges might feel frustrating, they are stepping stones that lead us to grow and uncover the true potential of AI.

3

The pyannote doesn’t ever starts with 0 is there any reason ?

4

感謝您的提問！您提到的「pyannote 不以 0 開始」的行為很有趣，這可能是由系統初始化或輸出處理方式所導致的。

Thank you for your question! The behavior you mentioned, “pyannote doesn’t ever start with 0,” is quite intriguing and might be caused by system initialization or output processing.

以下是一些可能的原因及建議：

Here are some potential reasons and suggestions:

  1. 初始化偏移：某些模型或應用程式的設計會將標籤從 1 開始，而非 0，這是一種常見的選擇，特別是在與其他工具整合時。

Initialization Offset: Some models or applications are designed to start labeling from 1 instead of 0, which is a common choice, especially when integrating with other tools.

  1. 配置問題：這可能與您所使用的 pyannote 配置、模型版本或環境設置有關。

Configuration Issue: This could relate to the pyannote configuration, model version, or environmental setup you are using.

  1. 輸出處理：某些場合中，輸出格式可能經過預處理，導致標籤偏移。

Output Processing: In certain cases, the output format might be preprocessed, leading to label offsets.

為了更準確地協助您，請提供以下資訊：

To assist you more accurately, could you provide the following details:

• 使用的 pyannote 模型版本

The version of the pyannote model you are using

• 您的程式碼片段（包含模型調用部分）

A snippet of your code (including the model invocation part)

• 執行的具體環境（如 Python 版本、是否使用 Colab 等）

The specific environment you are running (e.g., Python version, using Colab, etc.)

希望這些建議能幫助您解決問題！如果您仍然遇到困難，請隨時補充更多細節，我們可以一起探索更好的解決方案。

I hope these suggestions help you resolve your issue! If you still face difficulties, feel free to share more details, and we can explore better solutions together.

技術挑戰的過程，雖然可能伴隨著挫折，但正是它讓我們成長，並更好地了解 AI 的強大潛力。

While technical challenges might feel frustrating, they are stepping stones that lead us to grow and uncover the true potential of AI.