arthur630-tech/mob – Run with an API on Replicate

arthur630-tech / mob

Cold

Public
1.2K runs
L40S

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Run with an API

Playground API Examples README Versions

Input

prompt

*string

Shift + Return to add a new line

Text prompt to send to the model.

integer

(minimum: 1, maximum: 5)

Number of output sequences to generate

Default: 1

max_length

integer

(minimum: 1)

Maximum number of tokens to generate. A word is generally 2-3 tokens

Default: 50

temperature

number

(minimum: 0.01, maximum: 5)

Adjusts randomness of outputs, greater than 1 is random and 0 is deterministic, 0.75 is a good starting value.

Default: 0.75

top_p

number

(minimum: 0.01, maximum: 1)

When decoding text, samples from the top p percentage of most likely tokens; lower to ignore less likely tokens

Default: 1

repetition_penalty

number

(minimum: 0.01, maximum: 5)

Penalty for repeated words in generated text; 1 is no penalty, values greater than 1 discourage repetition, less than 1 encourage it.

Default: 1

top_k

integer

(minimum: 1)

计算每个可能的下一个 token 的概率分布

Default: 100

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

npx create-replicate --model=arthur630-tech/mob

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 arthur630-tech/mob using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "arthur630-tech/mob:209e2fde138326f89fdb246df01426ffd698560f66a4dc8d01736ecca98d2d97",
  {
    input: {
      n: 1,
      top_k: 100,
      top_p: 1,
      prompt: "你好呀",
      max_length: 50,
      temperature: 0.75,
      repetition_penalty: 1
    }
  }
);

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 arthur630-tech/mob using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "arthur630-tech/mob:209e2fde138326f89fdb246df01426ffd698560f66a4dc8d01736ecca98d2d97",
    input={
        "n": 1,
        "top_k": 100,
        "top_p": 1,
        "prompt": "你好呀",
        "max_length": 50,
        "temperature": 0.75,
        "repetition_penalty": 1
    }
)
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 arthur630-tech/mob 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": "arthur630-tech/mob:209e2fde138326f89fdb246df01426ffd698560f66a4dc8d01736ecca98d2d97",
    "input": {
      "n": 1,
      "top_k": 100,
      "top_p": 1,
      "prompt": "你好呀",
      "max_length": 50,
      "temperature": 0.75,
      "repetition_penalty": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

你好呀！我叫李红，是中国上海的。上海是中国最大的城市，人口有14亿人。这里有很多现代化的建筑，上海有很多世界级的博物馆，例如上海博物馆。上海还非常擅

Generated in

3.9 seconds

Tweak it Share Report

Run time and cost

This model costs approximately $0.010 to run on Replicate, or 100 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 L40S GPU hardware. Predictions typically complete within 11 seconds.

Readme

This model doesn't have a readme.