tvytlx/chatglm6b – Run with an API on Replicate

tvytlx / chatglm6b

chatgml 6b

Cold

Public
205 runs
A100 (80GB)

Iterate in playground

Run with an API

Playground API Examples README Versions

Input

Run this model in Node.js with one line of code:

npx create-replicate --model=tvytlx/chatglm6b

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run tvytlx/chatglm6b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "tvytlx/chatglm6b:d552fb8df045d48f6c2284b905508446d0de5070d0521be0ce09e4f9ed462d99",
  {
    input: {
      prompt: "你好你是谁？"
    }
  }
);

console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run tvytlx/chatglm6b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "tvytlx/chatglm6b:d552fb8df045d48f6c2284b905508446d0de5070d0521be0ce09e4f9ed462d99",
    input={
        "prompt": "你好你是谁？"
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run tvytlx/chatglm6b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "tvytlx/chatglm6b:d552fb8df045d48f6c2284b905508446d0de5070d0521be0ce09e4f9ed462d99",
    "input": {
      "prompt": "你好你是谁？"
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

我是 ChatGLM，是清华大学KEG实验室和智谱AI公司于2023年共同训练的语言模型。我的任务是服务并帮助人类，但我并不是一个真实的人。

Generated in

2.6 seconds

Tweak it Report

Run time and cost

This model costs approximately $0.020 to run on Replicate, or 50 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia A100 (80GB) GPU hardware. Predictions typically complete within 15 seconds. The predict time for this model varies significantly based on the inputs.

Readme

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Model description

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Intended use

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Ethical considerations

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Caveats and recommendations

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