nateraw/axolotl-llama-2-7b-english-to-hinglish – Run with an API on Replicate

nateraw / axolotl-llama-2-7b-english-to-hinglish

Cold

Public
298 runs
L40S

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: 0.7

do_sample

boolean

Whether or not to use sampling; otherwise use greedy decoding.

Default: true

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

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

### Instruction:
Translate the input from English to Hinglish

### Input:
{prompt}

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

### Instruction:
Translate the input from English to Hinglish

### Input:
{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: "### System:\nBelow is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\nTranslate the input from English to Hinglish\n\n### Input:\n{prompt}\n\n### Response:\n "

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

npx create-replicate --model=nateraw/axolotl-llama-2-7b-english-to-hinglish

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-llama-2-7b-english-to-hinglish using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "nateraw/axolotl-llama-2-7b-english-to-hinglish:03c8cc6582309c28ec5fdea84c94f49085fb105a1137f4771525376a88d8d95f",
  {
    input: {
      top_k: 50,
      top_p: 0.95,
      prompt: "What's happening?",
      do_sample: true,
      temperature: 0.9,
      max_new_tokens: 512,
      prompt_template: "### System:\nBelow is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\nTranslate the input from English to Hinglish\n\n### Input:\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-llama-2-7b-english-to-hinglish using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "nateraw/axolotl-llama-2-7b-english-to-hinglish:03c8cc6582309c28ec5fdea84c94f49085fb105a1137f4771525376a88d8d95f",
    input={
        "top_k": 50,
        "top_p": 0.95,
        "prompt": "What's happening?",
        "do_sample": True,
        "temperature": 0.9,
        "max_new_tokens": 512,
        "prompt_template": "### System:\nBelow is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\nTranslate the input from English to Hinglish\n\n### Input:\n{prompt}\n\n### Response:\n"
    }
)

# The nateraw/axolotl-llama-2-7b-english-to-hinglish 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-llama-2-7b-english-to-hinglish/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-llama-2-7b-english-to-hinglish 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": "03c8cc6582309c28ec5fdea84c94f49085fb105a1137f4771525376a88d8d95f",
    "input": {
      "top_k": 50,
      "top_p": 0.95,
      "prompt": "What\'s happening?",
      "do_sample": true,
      "temperature": 0.9,
      "max_new_tokens": 512,
      "prompt_template": "### System:\\nBelow is an instruction that describes a task. Write a response that appropriately completes the request.\\n\\n### Instruction:\\nTranslate the input from English to Hinglish\\n\\n### Input:\\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.

Output

kya ho raha hai?

Generated in

0.6 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. The predict time for this model varies significantly based on the inputs.

Readme

This model doesn't have a readme.