01-ai/yi-34b – Run with an API on Replicate

01-ai / yi-34b

The Yi series models are large language models trained from scratch by developers at 01.AI.

Cold

Public
3.7K runs
L40S
GitHub
License

Run with an API

Playground API Examples README Versions

Input

prompt

*string

Shift + Return to add a new line

max_new_tokens

integer

The maximum number of tokens the model should generate as output.

Default: 512

temperature

number

The value used to modulate the next token probabilities.

Default: 0.8

top_p

number

A probability threshold for generating the output. If < 1.0, only keep the top tokens with cumulative probability >= top_p (nucleus filtering). Nucleus filtering is described in Holtzman et al. (http://arxiv.org/abs/1904.09751).

Default: 0.95

top_k

integer

The number of highest probability tokens to consider for generating the output. If > 0, only keep the top k tokens with highest probability (top-k filtering).

Default: 50

presence_penalty

number

Presence penalty

Default: 0

frequency_penalty

number

Frequency penalty

Default: 0

prompt_template

string

Shift + Return to add a new line

The template used to format the prompt. The input prompt is inserted into the template using the `{prompt}` placeholder.

Default: "{prompt}"

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

npx create-replicate --model=01-ai/yi-34b

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 01-ai/yi-34b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "01-ai/yi-34b:d83ccf090ccd5c7fe507ca302a558a850468293385d02bb807ee2753d802dd85",
  {
    input: {
      top_k: 50,
      top_p: 0.95,
      prompt: "Some great names for dogs are:",
      temperature: 0.8,
      max_new_tokens: 128,
      prompt_template: "{prompt}",
      presence_penalty: 0,
      frequency_penalty: 0
    }
  }
);

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 01-ai/yi-34b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "01-ai/yi-34b:d83ccf090ccd5c7fe507ca302a558a850468293385d02bb807ee2753d802dd85",
    input={
        "top_k": 50,
        "top_p": 0.95,
        "prompt": "Some great names for dogs are:",
        "temperature": 0.8,
        "max_new_tokens": 128,
        "prompt_template": "{prompt}",
        "presence_penalty": 0,
        "frequency_penalty": 0
    }
)

# The 01-ai/yi-34b 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/01-ai/yi-34b/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 01-ai/yi-34b 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": "d83ccf090ccd5c7fe507ca302a558a850468293385d02bb807ee2753d802dd85",
    "input": {
      "top_k": 50,
      "top_p": 0.95,
      "prompt": "Some great names for dogs are:",
      "temperature": 0.8,
      "max_new_tokens": 128,
      "prompt_template": "{prompt}",
      "presence_penalty": 0,
      "frequency_penalty": 0
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

1.Lobo 2.Santana 3.Juice 4.Pearl 5.Pepper 6.Cash 7.Jager 8.Beer 9.Jack 10.Lucky 11.Beau 12.Boo 13.Dude 14.Cocoa 15.Piggy 16.Gypsy 17.Mocha 18.Lucy 19.Bud 20.Chi 21.ChiChi 22.M

{
  "completed_at": "2023-11-14T20:40:31.355627Z",
  "created_at": "2023-11-14T20:40:26.645336Z",
  "data_removed": false,
  "error": null,
  "id": "r7rbtl3brdn6sg3mw6jldtqm2i",
  "input": {
    "top_k": 50,
    "top_p": 0.95,
    "prompt": "Some great names for dogs are:",
    "temperature": 0.8,
    "max_new_tokens": 128,
    "prompt_template": "{prompt}",
    "presence_penalty": 0,
    "frequency_penalty": 0
  },
  "logs": "Generated 128 tokens in 4.597692012786865 seconds.",
  "metrics": {
    "predict_time": 4.668595,
    "total_time": 4.710291
  },
  "output": [
    "\n",
    "1",
    ".",
    "L",
    "obo",
    "\n",
    "2",
    ".",
    "S",
    "ant",
    "ana",
    "\n",
    "3",
    ".",
    "J",
    "u",
    "ice",
    "\n",
    "4",
    ".",
    "P",
    "ear",
    "l",
    "\n",
    "5",
    ".",
    "Pe",
    "pper",
    "\n",
    "6",
    ".",
    "C",
    "ash",
    "\n",
    "7",
    ".",
    "J",
    "ager",
    "\n",
    "8",
    ".",
    "Be",
    "er",
    "\n",
    "9",
    ".",
    "Jack",
    "\n",
    "1",
    "0",
    ".",
    "L",
    "ucky",
    "\n",
    "1",
    "1",
    ".",
    "Be",
    "au",
    "\n",
    "1",
    "2",
    ".",
    "B",
    "oo",
    "\n",
    "1",
    "3",
    ".",
    "D",
    "ude",
    "\n",
    "1",
    "4",
    ".",
    "C",
    "ocoa",
    "\n",
    "1",
    "5",
    ".",
    "P",
    "ig",
    "gy",
    "\n",
    "1",
    "6",
    ".",
    "G",
    "y",
    "psy",
    "\n",
    "1",
    "7",
    ".",
    "M",
    "ocha",
    "\n",
    "1",
    "8",
    ".",
    "Lu",
    "cy",
    "\n",
    "1",
    "9",
    ".",
    "B",
    "ud",
    "\n",
    "2",
    "0",
    ".",
    "Ch",
    "i",
    "\n",
    "2",
    "1",
    ".",
    "Ch",
    "i",
    "Ch",
    "i",
    "\n",
    "2",
    "2",
    ".",
    "M"
  ],
  "started_at": "2023-11-14T20:40:26.687032Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/r7rbtl3brdn6sg3mw6jldtqm2i",
    "cancel": "https://api.replicate.com/v1/predictions/r7rbtl3brdn6sg3mw6jldtqm2i/cancel"
  },
  "version": "d83ccf090ccd5c7fe507ca302a558a850468293385d02bb807ee2753d802dd85"
}

Generated in

4.7 seconds

Tweak it Report

Run time and cost

This model costs approximately $0.00098 to run on Replicate, or 1020 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 1 seconds.

Readme

See the full model card here

The model served here is the AWQ quantized version from here. Thank you to @TheBloke for sharing this model!

NOTE: As per the license, replicate was granted permission to share the model here.