dsingal0 / stablecode-completion-alpha-3b-4k

Cold

Public
48 runs
L40S

Run with an API

Playground API Examples README Versions

Prediction

dsingal0/stablecode-completion-alpha-3b-4k:fbecedaf

Model

dsingal0/stablecode-completion-alpha-3b-4k:fbecedaf

hdp4573bydxqvxh2hu7ieqmwh4

Status

Succeeded

Source

Web

Hardware

A40

Total duration

1m 49s

Created

over 1 year ago by @dsingal0

Input

text: import torch.nn as nn
temperature: 0.2
max_new_tokens: 100

{
  "text": "import torch.nn as nn",
  "temperature": 0.2,
  "max_new_tokens": 100
}

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 dsingal0/stablecode-completion-alpha-3b-4k using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "dsingal0/stablecode-completion-alpha-3b-4k:fbecedaf4d824f6de70b2075ba8a35ee306f37b37a335cc839ce75a9e44d0039",
  {
    input: {
      text: "import torch.nn as nn",
      temperature: 0.2,
      max_new_tokens: 100
    }
  }
);
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 dsingal0/stablecode-completion-alpha-3b-4k using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "dsingal0/stablecode-completion-alpha-3b-4k:fbecedaf4d824f6de70b2075ba8a35ee306f37b37a335cc839ce75a9e44d0039",
    input={
        "text": "import torch.nn as nn",
        "temperature": 0.2,
        "max_new_tokens": 100
    }
)
print(output)

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 dsingal0/stablecode-completion-alpha-3b-4k 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": "fbecedaf4d824f6de70b2075ba8a35ee306f37b37a335cc839ce75a9e44d0039",
    "input": {
      "text": "import torch.nn as nn",
      "temperature": 0.2,
      "max_new_tokens": 100
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Install Cog

brew install cog

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

Pull and run dsingal0/stablecode-completion-alpha-3b-4k using Cog (this will download the full model and run it in your local environment):

cog predict r8.im/dsingal0/stablecode-completion-alpha-3b-4k@sha256:fbecedaf4d824f6de70b2075ba8a35ee306f37b37a335cc839ce75a9e44d0039 \
  -i 'text="import torch.nn as nn"' \
  -i 'temperature=0.2' \
  -i 'max_new_tokens=100'

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

Pull and run dsingal0/stablecode-completion-alpha-3b-4k using Docker (this will download the full model and run it in your local environment):

docker run -d -p 5000:5000 --gpus=all r8.im/dsingal0/stablecode-completion-alpha-3b-4k@sha256:fbecedaf4d824f6de70b2075ba8a35ee306f37b37a335cc839ce75a9e44d0039
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "text": "import torch.nn as nn",
      "temperature": 0.2,
      "max_new_tokens": 100
    }
  }' \
  http://localhost:5000/predictions

Output

import torch.nn as nn import torch.nn.functional as F import torch.optim as optim from torch.autograd import Variable import torch import numpy as np import math from torch.utils.data import DataLoader from torchvision import datasets, transforms from torchvision.utils import save_image from torchvision.utils import make_grid from torchvision.utils import make_grid from torchvision.utils import save_image from torchvision.utils import make_grid from torchvision.

Generated in

4.0 seconds

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