Prediction

cbh123/samsum:2d1f4bf15916a2a93bc1068e72da42a71a05a9a6bfa3cd8f8d7077e22d83605f

Model

cbh123/samsum:2d1f4bf1

msodiedbf67kxi26j4gazeolpm

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

68.9s

Created

almost 2 years ago

Input

debug
top_k: 50
top_p: 0.9
prompt: Input: Amanda: I baked cookies. Do you want some? Jerry: Sure! Amanda: I'll bring you tomorrow :-) [/INST] Summary:
temperature: 0.75
max_new_tokens: 128
min_new_tokens: -1

{
  "debug": false,
  "top_k": 50,
  "top_p": 0.9,
  "prompt": "Input:\nAmanda: I baked  cookies. Do you want some?\nJerry: Sure!\nAmanda: I'll bring you tomorrow :-) [/INST]\n\nSummary: ",
  "temperature": 0.75,
  "max_new_tokens": 128,
  "min_new_tokens": -1
}

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 cbh123/samsum using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "cbh123/samsum:2d1f4bf15916a2a93bc1068e72da42a71a05a9a6bfa3cd8f8d7077e22d83605f",
  {
    input: {
      debug: false,
      top_k: 50,
      top_p: 0.9,
      prompt: "Input:\nAmanda: I baked  cookies. Do you want some?\nJerry: Sure!\nAmanda: I'll bring you tomorrow :-) [/INST]\n\nSummary: ",
      temperature: 0.75,
      max_new_tokens: 128,
      min_new_tokens: -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 cbh123/samsum using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "cbh123/samsum:2d1f4bf15916a2a93bc1068e72da42a71a05a9a6bfa3cd8f8d7077e22d83605f",
    input={
        "debug": False,
        "top_k": 50,
        "top_p": 0.9,
        "prompt": "Input:\nAmanda: I baked  cookies. Do you want some?\nJerry: Sure!\nAmanda: I'll bring you tomorrow :-) [/INST]\n\nSummary: ",
        "temperature": 0.75,
        "max_new_tokens": 128,
        "min_new_tokens": -1
    }
)

# The cbh123/samsum model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
    # https://replicate.com/cbh123/samsum/api#output-schema
    print(item, end="")

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 cbh123/samsum 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": "cbh123/samsum:2d1f4bf15916a2a93bc1068e72da42a71a05a9a6bfa3cd8f8d7077e22d83605f",
    "input": {
      "debug": false,
      "top_k": 50,
      "top_p": 0.9,
      "prompt": "Input:\\nAmanda: I baked  cookies. Do you want some?\\nJerry: Sure!\\nAmanda: I\'ll bring you tomorrow :-) [/INST]\\n\\nSummary: ",
      "temperature": 0.75,
      "max_new_tokens": 128,
      "min_new_tokens": -1
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Amanda will bring Jerry some cookies tomorrow..</s>

Generated in

1.1 seconds

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