coffee-25000ckpt-chunk50

# Model Card for Model ID

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## Model Details

### Model Description

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### Model Sources [optional]

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## Uses

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### 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

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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.

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## 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]

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## Evaluation

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### 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

<!-- 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]
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## 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]

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**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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### Framework versions

- PEFT 0.11.1

# 模型编号对应的模型卡片
<!-- 简要概述该模型的本质与功能 -->

## 模型详情
### 模型描述
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- **开发方：** [More Information Needed]
- **资助方（可选）：** [More Information Needed]
- **分享方（可选）：** [More Information Needed]
- **模型类型：** [More Information Needed]
- **（自然语言处理，NLP）覆盖语言：** [More Information Needed]
- **许可证：** [More Information Needed]
- **基于下述模型微调而来（可选）：** [More Information Needed]

### 模型来源（可选）
<!-- 提供该模型的基础链接信息 -->

- **代码仓库：** [More Information Needed]
- **相关论文（可选）：** [More Information Needed]
- **演示（Demo）（可选）：** [More Information Needed]

## 模型用途
<!-- 说明该模型的预期使用场景，包括可预见的使用者与受该模型影响的群体。 -->

### 直接使用
<!-- 本节说明无需微调或接入更大生态/应用的模型使用方式。 -->

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### 下游使用（可选）
<!-- 本节说明针对特定任务微调，或接入更大生态/应用的模型使用方式。 -->

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### 超范围使用
<!-- 本节说明误用、恶意使用，以及模型无法良好适配的使用场景。 -->

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## 偏见、风险与局限性
<!-- 本节旨在说明技术与社会技术层面的局限性。 -->

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### 建议
<!-- 本节旨在针对模型的偏见、风险与技术局限性给出相关建议。 -->

无论是直接使用者还是下游使用者，均应知悉该模型存在的风险、偏见与局限性，进一步的建议尚需补充更多信息。

## 模型快速上手指南
可通过下述代码快速上手该模型。

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## 训练详情
### 训练数据
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### 训练流程
<!-- 本节内容与技术规格紧密相关，如与训练流程相关的内容应链接至对应章节。 -->

#### 预处理（可选）
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#### 训练超参数
- **训练模式：** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

#### 运行速度、模型规模与耗时（可选）
<!-- 本节提供吞吐量、启动/结束时间、相关检查点大小等信息。 -->

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## 模型评估
<!-- 本节描述评估协议并提供评估结果。 -->

### 测试数据、评估维度与指标
#### 测试数据
<!-- 如有可能，此处应链接至数据集卡片。 -->

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#### 评估维度
<!-- 指评估时所拆分的维度，例如子群体或应用领域。 -->

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#### 评估指标
<!-- 指本次评估所使用的指标，最好附带选择该指标的原因说明。 -->

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### 评估结果
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#### 总结

## 模型可解释性分析（可选）
<!-- 本节收录与模型可解释性相关的研究工作。 -->

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## 环境影响
<!-- 此处应填写总碳排放量（以CO₂当量克数为单位）及其他相关信息，例如电力消耗情况，请编辑下述示例文本。 -->

碳排放量可通过[Lacoste等人(2019)]提出的[机器学习碳排放计算器(Machine Learning Impact calculator)](https://mlco2.github.io/impact#compute)进行估算，相关论文链接为[Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700)。

- **硬件类型：** [More Information Needed]
- **训练时长：** [More Information Needed]
- **云服务提供商：** [More Information Needed]
- **计算区域：** [More Information Needed]
- **碳排放量：** [More Information Needed]

## 技术规格（可选）
### 模型架构与训练目标
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### 计算基础设施
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#### 硬件
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#### 软件
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## 引用信息（可选）
<!-- 如存在介绍该模型的论文或博客文章，本节应收录其APA与BibTeX格式引用信息。 -->

**BibTeX格式引用：**

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**APA格式引用：**

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## 术语表（可选）
<!-- 如有需要，本节可收录有助于读者理解模型或模型卡片的术语与计算公式。 -->

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## 更多信息（可选）
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## 模型卡片撰写者（可选）
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## 模型卡片联系人
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### 框架版本
- 参数高效微调（PEFT, Parameter-Efficient Fine-Tuning）0.11.1