new_30000steps

# Model Card for Model ID

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## Model Details

### Model Description

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- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]

### Model Sources [optional]

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- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]

## Uses

<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->

### Direct Use

<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->

[More Information Needed]

### Downstream Use [optional]

<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->

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### Out-of-Scope Use

<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->

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## Bias, Risks, and Limitations

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[More Information Needed]

### Recommendations

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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

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### Training Procedure

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#### Preprocessing [optional]

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#### Training Hyperparameters

- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

#### Speeds, Sizes, Times [optional]

<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->

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## Evaluation

<!-- This section describes the evaluation protocols and provides the results. -->

### Testing Data, Factors & Metrics

#### Testing Data

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#### Factors

<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->

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#### Metrics

<!-- These are the evaluation metrics being used, ideally with a description of why. -->

[More Information Needed]

### Results

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#### Summary

## Model Examination [optional]

<!-- Relevant interpretability work for the model goes here -->

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## Environmental Impact

<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->

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

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#### Hardware

[More Information Needed]

#### Software

[More Information Needed]

## Citation [optional]

<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

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**APA:**

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## Glossary [optional]

<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->

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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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### Framework versions

- PEFT 0.11.1

# 针对模型编号的模型卡片
<!-- 简要概述该模型的定义与功能 -->

## 模型详情

### 模型描述
<!-- 详细说明该模型的具体定义 -->

- **开发者：** [需补充更多信息]
- **资助方（可选）：** [需补充更多信息]
- **分享方（可选）：** [需补充更多信息]
- **模型类型：** [需补充更多信息]
- **自然语言处理（NLP）相关语言：** [需补充更多信息]
- **授权协议：** [需补充更多信息]
- **基于以下模型微调（可选）：** [需补充更多信息]

### 模型来源（可选）
<!-- 提供该模型的基础链接 -->

- **代码仓库：** [需补充更多信息]
- **相关论文（可选）：** [需补充更多信息]
- **演示 Demo（可选）：** [需补充更多信息]

## 模型用途
<!-- 解答该模型的预期使用场景，包括可预见的使用者与受影响群体 -->

### 直接使用
<!-- 该部分用于描述无需微调或接入更大生态/应用的模型使用方式 -->
[需补充更多信息]

### 下游应用（可选）
<!-- 该部分用于描述为特定任务微调后，或接入更大生态/应用的模型使用方式 -->
[需补充更多信息]

### 超出范围的使用场景
<!-- 该部分说明误用、恶意使用，以及模型表现不佳的使用场景 -->
[需补充更多信息]

## 偏差、风险与局限性
<!-- 该部分用于说明技术与社会技术层面的局限性 -->
[需补充更多信息]

### 建议事项
<!-- 该部分用于给出针对偏差、风险与技术局限性的相关建议 -->
无论是直接使用者还是下游使用者，均应知晓该模型存在的风险、偏差与局限性，相关建议仍需补充更多信息以完善。

## 如何快速上手该模型
可通过以下代码快速启动该模型。
[需补充更多信息]

## 训练详情

### 训练数据
<!-- 此处应链接至数据集卡片，可附带简短说明训练数据的核心内容，以及数据预处理、额外筛选相关的文档 -->
[需补充更多信息]

### 训练流程
<!-- 该部分与技术规范高度相关，相关内容应链接至对应章节 -->
#### 预处理（可选）
[需补充更多信息]

#### 训练超参数
- **训练策略：** [需补充更多信息] <!--fp32、fp16混合精度、bf16混合精度、bf16非混合精度、fp16非混合精度、fp8混合精度 -->

#### 速度、规模与耗时（可选）
<!-- 该部分提供吞吐量、启动/结束时间、相关检查点大小等信息 -->
[需补充更多信息]

## 模型评估
<!-- 该部分描述评估协议与评估结果 -->
### 测试数据、评估维度与评估指标
#### 测试数据
<!-- 如有可能，此处应链接至数据集卡片 -->
[需补充更多信息]

#### 评估维度
<!-- 指评估时所拆分的维度，例如子群体或应用领域 -->
[需补充更多信息]

#### 评估指标
<!-- 指所使用的评估指标，理想情况下应说明选择原因 -->
[需补充更多信息]

### 评估结果
[需补充更多信息]

#### 总结

## 模型可解释性分析（可选）
<!-- 此处收录与模型可解释性相关的研究内容 -->
[需补充更多信息]

## 环境影响
<!-- 此处应填写总碳排放量（以克CO₂当量计）与其他相关信息，例如电力消耗。请编辑以下建议文本 -->
可通过[机器学习影响计算器](https://mlco2.github.io/impact#compute)估算碳排放量，该工具由[Lacoste等人（2019）](https://arxiv.org/abs/1910.09700)提出。

- **硬件类型：** [需补充更多信息]
- **使用时长：** [需补充更多信息]
- **云服务提供商：** [需补充更多信息]
- **计算区域：** [需补充更多信息]
- **碳排放量：** [需补充更多信息]

## 技术规范（可选）
### 模型架构与训练目标
[需补充更多信息]

### 计算基础设施
[需补充更多信息]
#### 硬件
[需补充更多信息]
#### 软件
[需补充更多信息]

## 引用信息（可选）
<!-- 若存在介绍该模型的论文或博客文章，此处应收录其APA与BibTeX格式的引用信息 -->
**BibTeX格式引用：**

[需补充更多信息]

**APA格式引用：**

[需补充更多信息]

## 术语表（可选）
<!-- 如有需要，可在此处收录有助于读者理解该模型或模型卡片的术语与计算公式 -->
[需补充更多信息]

## 更多信息（可选）
[需补充更多信息]

## 模型卡片作者（可选）
[需补充更多信息]

## 模型卡片联系方式
[需补充更多信息]
### 框架版本
- 参数高效微调（PEFT） 0.11.1