orca-mini:13b-v2-q4_K_S

Orca Mini 是一个基于 Llama 和 Llama 2 模型训练的模型，训练数据为 Orca Style 数据集，该数据集使用论文《Orca: Progressive Learning from Complex Explanation Traces of GPT-4》中定义的方法创建。有两个版本。原始 Orca Mini 基于 Llama，参数大小为 30 亿、70 亿和 130 亿，v3 版本基于 Llama 2，参数大小为 70 亿、130 亿和 700 亿。

用法

CLI

打开终端并运行 ollama run orca-mini

API

示例

  curl -X POST http://127.0.0.1:11434/api/generate -d '{
    "model": "orca-mini",
    "prompt":"Why is the sky blue?"
   }'

内存要求

70 亿参数模型通常至少需要 8GB 内存
130 亿参数模型通常至少需要 16GB 内存
700 亿参数模型通常至少需要 64GB 内存

参考

30 亿参数原始来源: Pankaj Mathur

70 亿参数原始来源: Pankaj Mathur

130 亿参数原始来源: Pankaj Mathur

Ollama 上的 Orca Mini v3 来源

130 亿参数原始来源: Pankaj Mathur

700 亿参数来源: Pankaj Mathur

Orca: 从 GPT-4 复杂解释轨迹的渐进学习

Orca Mini is a Llama and Llama 2 model trained on Orca Style datasets created using the approaches defined in the paper, Orca: Progressive Learning from Complex Explanation Traces of GPT-4. There are two variations available. The original Orca Mini based on Llama in 3, 7, and 13 billion parameter sizes, and v3 based on Llama 2 in 7, 13, and 70 billion parameter sizes.

## Usage

### CLI

Open the terminal and run `ollama run orca-mini`

### API

Example:

```bash
  curl -X POST http://127.0.0.1:11434/api/generate -d '{
    "model": "orca-mini",
    "prompt":"Why is the sky blue?"
   }'
  ```

## Memory requirements

- 7b models generally require at least 8GB of RAM
- 13b models generally require at least 16GB of RAM
- 70b models generally require at least 64GB of RAM

## Reference

3b parameters original source:
 [Pankaj Mathur](http://hugging-face.cn/psmathur/orca_mini_3b)

7b parameters original source:
 [Pankaj Mathur](http://hugging-face.cn/psmathur/orca_mini_7b)

13b parameters original source:
 [Pankaj Mathur](http://hugging-face.cn/psmathur/orca_mini_13b)

**Orca Mini v3 source on Ollama**

13b parameters original source:
 [Pankaj Mathur](http://hugging-face.cn/psmathur/orca_mini_v3_13b)

70b parameters source:
 [Pankaj Mathur](http://hugging-face.cn/psmathur/orca_mini_v3_70b)

[Orca: Progressive Learning from Complex Explanation Traces of GPT-4](https://arxiv.org/abs/2306.02707 )

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