Prediction

arthur630-tech/mob:209e2fde138326f89fdb246df01426ffd698560f66a4dc8d01736ecca98d2d97

Model

arthur630-tech/mob:209e2fde

3wevhtqqt9rj60ckv7gs2drmtr

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

2m 29s

Created

8 months ago

Input

n: 1
top_k: 100
top_p: 1
prompt: 你好呀
max_length: 50
temperature: 0.75
repetition_penalty: 1

{
  "n": 1,
  "top_k": 100,
  "top_p": 1,
  "prompt": "你好呀",
  "max_length": 50,
  "temperature": 0.75,
  "repetition_penalty": 1
}

Install Replicate’s Node.js client library:

npm install replicate

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

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.

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.

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/arthur630-tech/mob@sha256:209e2fde138326f89fdb246df01426ffd698560f66a4dc8d01736ecca98d2d97 \
  -i 'n=1' \
  -i 'top_k=100' \
  -i 'top_p=1' \
  -i 'prompt="你好呀"' \
  -i 'max_length=50' \
  -i 'temperature=0.75' \
  -i 'repetition_penalty=1'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/arthur630-tech/mob@sha256:209e2fde138326f89fdb246df01426ffd698560f66a4dc8d01736ecca98d2d97
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "n": 1,
      "top_k": 100,
      "top_p": 1,
      "prompt": "你好呀",
      "max_length": 50,
      "temperature": 0.75,
      "repetition_penalty": 1
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

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

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