technillogue/llama-2-7b-chat-hf-mlc:147a3c83 | Run with an API on Replicate

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technillogue /llama-2-7b-chat-hf-mlc:147a3c83

Playground API

Input

prompt

*string

Shift + Return to add a new line

Prompt to send to the model.

system_prompt

string

Shift + Return to add a new line

You are a helpful, respectful and honest assistant.You are a helpful, respectful and honest assistant.

System prompt to send to the model. This is prepended to the prompt and helps guide system behavior. Should not be blank.

Default: "You are a helpful, respectful and honest assistant."

max_new_tokens

integer

(minimum: 1)

Maximum number of tokens to generate. A word is generally 2-3 tokens

Default: 128

min_new_tokens

integer

(minimum: -1)

Minimum number of tokens to generate. To disable, set to -1. A word is generally 2-3 tokens.

Default: -1

temperature

number

(minimum: 0.01, maximum: 5)

Adjusts randomness of outputs, greater than 1 is random and 0 is deterministic, 0.75 is a good starting value.

Default: 0.7

top_p

number

(minimum: 0, maximum: 1)

When decoding text, samples from the top p percentage of most likely tokens; lower to ignore less likely tokens

Default: 0.95

repetition_penalty

number

(minimum: 0)

A parameter that controls how repetitive text can be. Lower means more repetitive, while higher means less repetitive. Set to 1.0 to disable.

Default: 1.15

stop_sequences

string

Shift + Return to add a new line

A comma-separated list of sequences to stop generation at. For example, '<end>,<stop>' will stop generation at the first instance of 'end' or '<stop>'.

seed

integer

Random seed. Leave blank to randomize the seed

debug

boolean

provide debugging output in logs

Default: false

prompt_template

string

Shift + Return to add a new line

[INST] <<SYS>>
{system_prompt}
<</SYS>>

{prompt} [/INST][INST] <<SYS>>
{system_prompt}
<</SYS>>

{prompt} [/INST]

Template for formatting the prompt

Default: "[INST] <<SYS>>\n{system_prompt}\n<</SYS>>\n\n{prompt} [/INST]"

disable_mlc_formatting

boolean

for debugging, do not use

Default: false

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

npx create-replicate --model=technillogue/llama-2-7b-chat-hf-mlc

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 technillogue/llama-2-7b-chat-hf-mlc using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "technillogue/llama-2-7b-chat-hf-mlc:147a3c83e93b12e16eda7f7d9b4ed84f71257b7c0e9b25323e33c754c8834e38",
  {
    input: {
      debug: false,
      top_p: 0.95,
      temperature: 0.7,
      system_prompt: "You are a helpful, respectful and honest assistant.",
      max_new_tokens: 128,
      min_new_tokens: -1,
      prompt_template: "[INST] <<SYS>>\n{system_prompt}\n<</SYS>>\n\n{prompt} [/INST]",
      repetition_penalty: 1.15,
      disable_mlc_formatting: false
    }
  }
);

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 technillogue/llama-2-7b-chat-hf-mlc using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "technillogue/llama-2-7b-chat-hf-mlc:147a3c83e93b12e16eda7f7d9b4ed84f71257b7c0e9b25323e33c754c8834e38",
    input={
        "debug": False,
        "top_p": 0.95,
        "temperature": 0.7,
        "system_prompt": "You are a helpful, respectful and honest assistant.",
        "max_new_tokens": 128,
        "min_new_tokens": -1,
        "prompt_template": "[INST] <<SYS>>\n{system_prompt}\n<</SYS>>\n\n{prompt} [/INST]",
        "repetition_penalty": 1.15,
        "disable_mlc_formatting": False
    }
)

# The technillogue/llama-2-7b-chat-hf-mlc 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/technillogue/llama-2-7b-chat-hf-mlc/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 technillogue/llama-2-7b-chat-hf-mlc 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": "technillogue/llama-2-7b-chat-hf-mlc:147a3c83e93b12e16eda7f7d9b4ed84f71257b7c0e9b25323e33c754c8834e38",
    "input": {
      "debug": false,
      "top_p": 0.95,
      "temperature": 0.7,
      "system_prompt": "You are a helpful, respectful and honest assistant.",
      "max_new_tokens": 128,
      "min_new_tokens": -1,
      "prompt_template": "[INST] <<SYS>>\\n{system_prompt}\\n<</SYS>>\\n\\n{prompt} [/INST]",
      "repetition_penalty": 1.15,
      "disable_mlc_formatting": false
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

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