wizardlm:70b-llama2-q4_K_S

wizardlm

基于Llama 2的通用模型。

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a5124a5418a3 · 39GB

{ "stop": [ "USER:", "ASSISTANT:" ] }

31B

模板

{{ .System }} USER: {{ .Prompt }} ASSISTANT:

45B

系统

一个好奇的用户和一个人工智能助手之间的对话。助手提供有用的，

154B

自述文件

WizardLM是由WizardLM训练的基于Llama 2的70B参数模型。

开始使用WizardLM

以下示例中使用的模型是WizardLM模型，具有70b参数，这是一个通用模型。

API

启动Ollama服务器 (运行 ollama serve)
运行模型

curl -X POST https://127.0.0.1:11434/api/generate -d '{
  "model": "wizardlm:70b-llama2-q4_0",
  "prompt":"Why is the sky blue?"
 }'

CLI

安装Ollama
打开终端并运行 ollama run wizardlm:70b-llama2-q4_0

注意：如果模型尚未下载，则ollama run命令会执行ollama pull。要在不运行模型的情况下下载模型，请使用ollama pull wizardlm:70b-llama2-q4_0

内存要求

70b模型通常需要至少64GB的RAM

如果遇到更高的量化级别的问题，请尝试使用q4模型或关闭任何占用大量内存的其他程序。

模型变体

默认情况下，Ollama使用4位量化。要尝试其他量化级别，请尝试其他标签。 q后面的数字表示用于量化的位数（即q4表示4位量化）。数字越高，模型越准确，但运行速度越慢，并且需要的内存越多。

模型来源

Ollama上的WizardLM源代码

70b参数来源: The Bloke

70b参数原始来源: WizardLM

WizardLM is a 70B parameter model based on Llama 2 trained by WizardLM.

## Get started with WizardLM

The model used in the example below is the WizardLM model, with 70b parameters, which is a general-use model.

### API

1. Start Ollama server (Run `ollama serve`)
2. Run the model

```bash
curl -X POST https://127.0.0.1:11434/api/generate -d '{
  "model": "wizardlm:70b-llama2-q4_0",
  "prompt":"Why is the sky blue?"
 }'
  ```

### CLI

1. Install Ollama
2. Open the terminal and run `ollama run wizardlm:70b-llama2-q4_0`

Note: The `ollama run` command performs an `ollama pull` if the model is not already downloaded. To download the model without running it, use `ollama pull wizardlm:70b-llama2-q4_0`

## Memory requirements

- 70b models generally require at least 64GB of RAM

If you run into issues with higher quantization levels, try using the q4 model or shut down any other programs that are using a lot of memory.

## Model variants

By default, Ollama uses 4-bit quantization. To try other quantization levels, please try the other tags. The number after the q represents the number of bits used for quantization (i.e. q4 means 4-bit quantization). The higher the number, the more accurate the model is, but the slower it runs, and the more memory it requires.

## Model source

**WizardLM source on Ollama**

70b parameters source:
 [The Bloke](https://hugging-face.cn/TheBloke/WizardLM-70B-V1.0-GGML)

70b parameters original source:
 [WizardLM](https://hugging-face.cn/WizardLM/WizardLM-70B-V1.0)

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