Model Card for AutoModel

AutoModel 是一个多模态模型，支持图像、文本和语音输入...

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3. 提供可下载文件

确保以下文件已上传到仓库，便于用户下载和运行：

• 模型权重文件（如 AutoModel.pth）。
• 配置文件（如 config.json）。
• 依赖文件（如 requirements.txt）。
• 运行脚本（如 run_model.py）。 widget:
• text: "Jens Peter Hansen kommer fra Danmark" 用户可以直接下载这些文件并运行模型。

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4. 自动运行模型的限制

Hugging Face Hub 本身不能自动运行上传的模型，但通过 Spaces 提供的接口可以解决这一问题。Spaces 能够运行托管的推理服务，让用户无需本地配置即可测试模型。

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推荐方法

• 快速测试：使用 Hugging Face Spaces 创建在线演示。
• 高级使用：在模型卡中提供完整的运行说明，允许用户本地运行模型。

通过这些方式，您可以让模型仓库既支持在线运行，也便于用户离线部署。

Uses

Direct Use

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Downstream Use [optional]

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Out-of-Scope Use

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Bias, Risks, and Limitations

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Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

Use the code below to get started with the model.

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Training Details

Training Data

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Training Procedure

Preprocessing [optional]

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Training Hyperparameters

• Training regime: [More Information Needed]

Speeds, Sizes, Times [optional]

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Evaluation

Testing Data, Factors & Metrics

Testing Data

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Factors

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Metrics

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Results

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Summary

Model Examination [optional]

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Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

• Hardware Type: [More Information Needed]
• Hours used: [More Information Needed]
• Cloud Provider: [More Information Needed]
• Compute Region: [More Information Needed]
• Carbon Emitted: [More Information Needed]

Technical Specifications [optional]

Model Architecture and Objective

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Compute Infrastructure

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Hardware

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Software

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Citation [optional]

BibTeX:

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APA:

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Glossary [optional]

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More Information [optional]

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Model Card Authors [optional]

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Model Card Contact

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