nateraw/axolotl-test – Run with an API on Replicate

nateraw / axolotl-test

Cold

Public
9 runs
L40S

Run with an API

Playground API Examples Train 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: 0.7

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

prompt_template

string

Shift + Return to add a new line

<s> ### System:
Below is an instruction that describes a task. Write a response that appropriately completes the request.

### Instruction:
{prompt}

### Response:
<s> ### System:
Below is an instruction that describes a task. Write a response that appropriately completes the request.

### Instruction:
{prompt}

### Response:

The template used to format the prompt before passing it to the model. For no template, you can set this to `{prompt}`.

Default: "<s> ### System:\nBelow is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n{prompt}\n\n### Response:\n"

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

npx create-replicate --model=nateraw/axolotl-test

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 nateraw/axolotl-test using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "nateraw/axolotl-test:f1deeaf0a1caf741294e5e86c7ced357f28260ddd94dfc6dd2d5629ce49e8499",
  {
    input: {
      top_k: 50,
      top_p: 0.95,
      temperature: 0.7,
      max_new_tokens: 512,
      prompt_template: "<s> ### System:\nBelow is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n{prompt}\n\n### Response:\n"
    }
  }
);
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 nateraw/axolotl-test using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "nateraw/axolotl-test:f1deeaf0a1caf741294e5e86c7ced357f28260ddd94dfc6dd2d5629ce49e8499",
    input={
        "top_k": 50,
        "top_p": 0.95,
        "temperature": 0.7,
        "max_new_tokens": 512,
        "prompt_template": "<s> ### System:\nBelow is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n{prompt}\n\n### Response:\n"
    }
)

# The nateraw/axolotl-test 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/nateraw/axolotl-test/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 nateraw/axolotl-test 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": "f1deeaf0a1caf741294e5e86c7ced357f28260ddd94dfc6dd2d5629ce49e8499",
    "input": {
      "top_k": 50,
      "top_p": 0.95,
      "temperature": 0.7,
      "max_new_tokens": 512,
      "prompt_template": "<s> ### System:\\nBelow is an instruction that describes a task. Write a response that appropriately completes the request.\\n\\n### Instruction:\\n{prompt}\\n\\n### Response:\\n"
    }
  }' \
  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/nateraw/axolotl-test@sha256:f1deeaf0a1caf741294e5e86c7ced357f28260ddd94dfc6dd2d5629ce49e8499 \
  -i 'top_k=50' \
  -i 'top_p=0.95' \
  -i 'temperature=0.7' \
  -i 'max_new_tokens=512' \
  -i $'prompt_template="<s> ### System:\\nBelow is an instruction that describes a task. Write a response that appropriately completes the request.\\n\\n### Instruction:\\n{prompt}\\n\\n### Response:\\n"'

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/nateraw/axolotl-test@sha256:f1deeaf0a1caf741294e5e86c7ced357f28260ddd94dfc6dd2d5629ce49e8499
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "top_k": 50,
      "top_p": 0.95,
      "temperature": 0.7,
      "max_new_tokens": 512,
      "prompt_template": "<s> ### System:\\nBelow is an instruction that describes a task. Write a response that appropriately completes the request.\\n\\n### Instruction:\\n{prompt}\\n\\n### Response:\\n"
    }
  }' \
  http://localhost:5000/predictions

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

Output

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

Run time and cost

This model runs on Nvidia L40S GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

This model doesn't have a readme.