Prediction

yorickvp/llava-v1.6-mistral-7b:19be067b

Model

yorickvp/llava-v1.6-mistral-7b:19be067b

s24aeawxasrgj0cgkzabtj53rc

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

2.9s

Created

9 months ago by @janghaludu

Input

image
top_p: 1
prompt: Reply in json format with the following keys - containsLines : True or False, colorsOfLines: array of str, numberOfLines: int, numberOfIntersectionPointsBetweenLines: int
history: []
max_tokens: 1024
temperature: 0.2

{
  "image": "https://replicate.delivery/pbxt/LFOkHr2gGAdPNIanHgR9W4NpYaMSyL605eBBtmTIhZ2ZYu9F/Screenshot%202024-07-11%20at%208.56.55%20AM.png",
  "top_p": 1,
  "prompt": "Reply in json format with the following keys - containsLines : True or False,  colorsOfLines: array of str, numberOfLines: int, numberOfIntersectionPointsBetweenLines: int",
  "history": [],
  "max_tokens": 1024,
  "temperature": 0.2
}

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 yorickvp/llava-v1.6-mistral-7b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "yorickvp/llava-v1.6-mistral-7b:19be067b589d0c46689ffa7cc3ff321447a441986a7694c01225973c2eafc874",
  {
    input: {
      image: "https://replicate.delivery/pbxt/LFOkHr2gGAdPNIanHgR9W4NpYaMSyL605eBBtmTIhZ2ZYu9F/Screenshot%202024-07-11%20at%208.56.55%20AM.png",
      top_p: 1,
      prompt: "Reply in json format with the following keys - containsLines : True or False,  colorsOfLines: array of str, numberOfLines: int, numberOfIntersectionPointsBetweenLines: int",
      max_tokens: 1024,
      temperature: 0.2
    }
  }
);
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 yorickvp/llava-v1.6-mistral-7b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "yorickvp/llava-v1.6-mistral-7b:19be067b589d0c46689ffa7cc3ff321447a441986a7694c01225973c2eafc874",
    input={
        "image": "https://replicate.delivery/pbxt/LFOkHr2gGAdPNIanHgR9W4NpYaMSyL605eBBtmTIhZ2ZYu9F/Screenshot%202024-07-11%20at%208.56.55%20AM.png",
        "top_p": 1,
        "prompt": "Reply in json format with the following keys - containsLines : True or False,  colorsOfLines: array of str, numberOfLines: int, numberOfIntersectionPointsBetweenLines: int",
        "max_tokens": 1024,
        "temperature": 0.2
    }
)

# The yorickvp/llava-v1.6-mistral-7b 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/yorickvp/llava-v1.6-mistral-7b/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 yorickvp/llava-v1.6-mistral-7b 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": "19be067b589d0c46689ffa7cc3ff321447a441986a7694c01225973c2eafc874",
    "input": {
      "image": "https://replicate.delivery/pbxt/LFOkHr2gGAdPNIanHgR9W4NpYaMSyL605eBBtmTIhZ2ZYu9F/Screenshot%202024-07-11%20at%208.56.55%20AM.png",
      "top_p": 1,
      "prompt": "Reply in json format with the following keys - containsLines : True or False,  colorsOfLines: array of str, numberOfLines: int, numberOfIntersectionPointsBetweenLines: int",
      "max_tokens": 1024,
      "temperature": 0.2
    }
  }' \
  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/yorickvp/llava-v1.6-mistral-7b@sha256:19be067b589d0c46689ffa7cc3ff321447a441986a7694c01225973c2eafc874 \
  -i 'image="https://replicate.delivery/pbxt/LFOkHr2gGAdPNIanHgR9W4NpYaMSyL605eBBtmTIhZ2ZYu9F/Screenshot%202024-07-11%20at%208.56.55%20AM.png"' \
  -i 'top_p=1' \
  -i 'prompt="Reply in json format with the following keys - containsLines : True or False,  colorsOfLines: array of str, numberOfLines: int, numberOfIntersectionPointsBetweenLines: int"' \
  -i 'max_tokens=1024' \
  -i 'temperature=0.2'

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/yorickvp/llava-v1.6-mistral-7b@sha256:19be067b589d0c46689ffa7cc3ff321447a441986a7694c01225973c2eafc874
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "image": "https://replicate.delivery/pbxt/LFOkHr2gGAdPNIanHgR9W4NpYaMSyL605eBBtmTIhZ2ZYu9F/Screenshot%202024-07-11%20at%208.56.55%20AM.png",
      "top_p": 1,
      "prompt": "Reply in json format with the following keys - containsLines : True or False,  colorsOfLines: array of str, numberOfLines: int, numberOfIntersectionPointsBetweenLines: int",
      "max_tokens": 1024,
      "temperature": 0.2
    }
  }' \
  http://localhost:5000/predictions

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

Output

```json { "containsLines": true, "colorsOfLines": ["red", "blue"], "numberOfLines": 4, "numberOfIntersectionPointsBetweenLines": 2 } ```

Generated in

2.9 seconds

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