orca2:13b - Ollama 框架

orca2

Orca 2 由微軟研究部門建構，是 Meta Llama 2 模型的微調版本。此模型旨在於推理方面表現出色。

7b 13b

63.8K 下載次數更新於 15 個月前

33 個標籤

更新於 15 個月前

15 個月前

a8dcfac3ac32 · 7.4GB

{ "num_ctx": 4096, "stop": [ "<|im_start", "<|im_end", "|im_start",

82B

範本

<|im_start|>system {{ .System }}<|im_end|> <|im_start|>user {{ .Prompt }}<|im_end|> <|im_start|>assi

106B

系統

您是 Orca，一個由微軟創建的 AI 語言模型。您是一位謹慎的助手。您會仔細地

215B

授權

MICROSOFT RESEARCH 授權條款如果您居住在美國，請閱讀「BINDING ARBIT

11kB

說明文件

Orca 2 模型由微軟研究院建構。它們基於 Meta 的 Llama 2 進行微調，使用合成數據集，該數據集旨在增強小型模型的推理能力。所有合成訓練數據均已使用 Microsoft Azure 內容篩選器進行審核。

使用案例

Orca 2 是一個有用的助手，可以在諸如針對您給定的數據進行推理、閱讀理解、數學問題解決和文本摘要等任務中提供答案。

此模型旨在於推理方面表現出色。

微軟研究院對此模型的預期用途是鼓勵進一步研究小型語言模型的開發、評估和對齊。

CLI

70 億參數模型

ollama run orca2

130 億參數模型

ollama run orca2:13b

API

範例

curl -X POST https://#:11434/api/generate -d '{
  "model": "orca2",
  "prompt":"Why is the sky blue?"
 }'

參考文獻

微軟研究院公告部落格
微軟研究院發表的論文，《Orca 2：教導小型語言模型如何推理》

Orca 2 models are built by Microsoft Research. They are fine-tuned on Meta's Llama 2 using a synthetic dataset that was created to enhance the small model's reasoning abilities. All synthetic training data was moderated using Microsoft Azure content filters.

### Use case

Orca 2 is a helpful assistant, and provides an answer in tasks such as reasoning over your given data, reading comprehension, math problem solving and text summarization.

The model is designed to excel particularly in reasoning.

Microsoft Research's intended purpose for this model is to encourage further research on the development, evaluation, and alignment of smaller language models.

### CLI

7 billion parameter model:

```
ollama run orca2
```

13 billion parameter model:

```
ollama run orca2:13b
```

### API

Example:

```bash
curl -X POST https://#:11434/api/generate -d '{
  "model": "orca2",
  "prompt":"Why is the sky blue?"
 }'
```

### References

- [Microsoft Research announcement blog](https://www.microsoft.com/en-us/research/blog/orca-2-teaching-small-language-models-how-to-reason/)

- Microsoft Research published paper, [Orca 2: Teaching Small Language Models How to Reason](https://arxiv.org/pdf/2311.11045.pdf)

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