01-ai/yi-34b-chat:914692bb – Run with an API on Replicate

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01-ai /yi-34b-chat:914692bb

Playground API

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: 1024

temperature

number

The value used to modulate the next token probabilities.

Default: 0.3

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: 0.8

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

repetition_penalty

number

Repetition penalty

Default: 1.2

prompt_template

string

Shift + Return to add a new line

<|im_start|>system
You are a helpful assistant<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
<|im_start|>system
You are a helpful assistant<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

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

Default: "<|im_start|>system\nYou are a helpful assistant<|im_end|>\n<|im_start|>user\n{prompt}<|im_end|>\n<|im_start|>assistant\n"

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

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

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-chat 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-chat:914692bbe8a8e2b91a4e44203e70d170c9c5ccc1359b283c84b0ec8d47819a46",
  {
    input: {
      top_k: 50,
      top_p: 0.8,
      temperature: 0.3,
      max_new_tokens: 1024,
      prompt_template: "<|im_start|>system\nYou are a helpful assistant<|im_end|>\n<|im_start|>user\n{prompt}<|im_end|>\n<|im_start|>assistant\n",
      repetition_penalty: 1.2
    }
  }
);
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-chat using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "01-ai/yi-34b-chat:914692bbe8a8e2b91a4e44203e70d170c9c5ccc1359b283c84b0ec8d47819a46",
    input={
        "top_k": 50,
        "top_p": 0.8,
        "temperature": 0.3,
        "max_new_tokens": 1024,
        "prompt_template": "<|im_start|>system\nYou are a helpful assistant<|im_end|>\n<|im_start|>user\n{prompt}<|im_end|>\n<|im_start|>assistant\n",
        "repetition_penalty": 1.2
    }
)

# The 01-ai/yi-34b-chat 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-chat/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-chat 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": "914692bbe8a8e2b91a4e44203e70d170c9c5ccc1359b283c84b0ec8d47819a46",
    "input": {
      "top_k": 50,
      "top_p": 0.8,
      "temperature": 0.3,
      "max_new_tokens": 1024,
      "prompt_template": "<|im_start|>system\\nYou are a helpful assistant<|im_end|>\\n<|im_start|>user\\n{prompt}<|im_end|>\\n<|im_start|>assistant\\n",
      "repetition_penalty": 1.2
    }
  }' \
  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/01-ai/yi-34b-chat@sha256:914692bbe8a8e2b91a4e44203e70d170c9c5ccc1359b283c84b0ec8d47819a46 \
  -i 'top_k=50' \
  -i 'top_p=0.8' \
  -i 'temperature=0.3' \
  -i 'max_new_tokens=1024' \
  -i $'prompt_template="<|im_start|>system\\nYou are a helpful assistant<|im_end|>\\n<|im_start|>user\\n{prompt}<|im_end|>\\n<|im_start|>assistant\\n"' \
  -i 'repetition_penalty=1.2'

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/01-ai/yi-34b-chat@sha256:914692bbe8a8e2b91a4e44203e70d170c9c5ccc1359b283c84b0ec8d47819a46
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "top_k": 50,
      "top_p": 0.8,
      "temperature": 0.3,
      "max_new_tokens": 1024,
      "prompt_template": "<|im_start|>system\\nYou are a helpful assistant<|im_end|>\\n<|im_start|>user\\n{prompt}<|im_end|>\\n<|im_start|>assistant\\n",
      "repetition_penalty": 1.2
    }
  }' \
  http://localhost:5000/predictions

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

Output

No output yet! Press "Submit" to start a prediction.