--- language: - en - zh license: apache-2.0 library_name: pytorch tags: - multimodal - vqa - text - audio datasets: - synthetic-dataset metrics: - accuracy - bleu - wer model-index: - name: AutoModel results: - task: type: vqa name: Visual Question Answering dataset: type: synthetic-dataset name: Synthetic Multimodal Dataset split: test metrics: - type: accuracy value: 85 --- # Model Card for AutoModel AutoModel 是一个多模态模型,支持图像、文本和语音输入... --- ### **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。 --- ### **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。 --- ### **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 [More Information Needed] ### Downstream Use [optional] [More Information Needed] ### Out-of-Scope Use [More Information Needed] ## Bias, Risks, and Limitations [More Information Needed] ### 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. [More Information Needed] ## Training Details ### Training Data [More Information Needed] ### Training Procedure #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] #### Speeds, Sizes, Times [optional] [More Information Needed] ## Evaluation ### Testing Data, Factors & Metrics #### Testing Data [More Information Needed] #### Factors [More Information Needed] #### Metrics [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] [More Information Needed] ## Environmental Impact Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **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 [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]