hayooucom/vision-model – Run with an API on Replicate

hayooucom / vision-model

This is phi-3-vision model , cost by time ,have fun~

Cold

Public
14.2K runs
L40S
GitHub
Paper
License

Run with an API

Playground API Examples README Versions

Input

prompt

string

Shift + Return to add a new line

Text prompt to send to the model.

Default: "hello ,who are you?"

max_new_tokens

integer

(minimum: 1, maximum: 128000)

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

Default: 200

max_tokens

integer

(minimum: 1, maximum: 128000)

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

Default: 45000

temperature

number

(minimum: 0, maximum: 5)

Adjusts randomness of outputs, greater than 1 is random and 0 is deterministic.

Default: 0.1

top_p

number

(minimum: 0.01, maximum: 1)

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

Default: 1

top_k

integer

When decoding text, samples from the top k most likely tokens; lower to ignore less likely tokens.

Default: 1

repetition_penalty

number

(minimum: 0.01, maximum: 10)

Penalty for repeated words in generated text; 1 is no penalty, values greater than 1 discourage repetition, less than 1 encourage it.

Default: 1.1

system_prompt

string

Shift + Return to add a new line

System prompt.

Default: "You are a helpful AI assistant."

image_url

string[]

https://support.content.office.net/en-us/media/3dd2b79b-9160-403d-9967-af893d17b580.png

public image url.

Default: []

image_base64

string[]

image data base64 if no image url,use this.

Default: []

seed

integer

The seed for the random number generator

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

npx create-replicate --model=hayooucom/vision-model

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

const output = await replicate.run(
  "hayooucom/vision-model:6afc892d5aa00e0e0883dec30f7a766fcf515c64090def9d173093ac343c2438",
  {
    input: {
      top_k: 1,
      top_p: 1,
      prompt: "please describe this image.",
      image_url: ["https://support.content.office.net/en-us/media/3dd2b79b-9160-403d-9967-af893d17b580.png"],
      max_tokens: 45000,
      temperature: 0.1,
      image_base64: [],
      system_prompt: "You are a helpful AI assistant.",
      max_new_tokens: 458,
      repetition_penalty: 1.1
    }
  }
);

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

output = replicate.run(
    "hayooucom/vision-model:6afc892d5aa00e0e0883dec30f7a766fcf515c64090def9d173093ac343c2438",
    input={
        "top_k": 1,
        "top_p": 1,
        "prompt": "please describe this image.",
        "image_url": ["https://support.content.office.net/en-us/media/3dd2b79b-9160-403d-9967-af893d17b580.png"],
        "max_tokens": 45000,
        "temperature": 0.1,
        "image_base64": [],
        "system_prompt": "You are a helpful AI assistant.",
        "max_new_tokens": 458,
        "repetition_penalty": 1.1
    }
)

# The hayooucom/vision-model 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/hayooucom/vision-model/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 hayooucom/vision-model 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": "hayooucom/vision-model:6afc892d5aa00e0e0883dec30f7a766fcf515c64090def9d173093ac343c2438",
    "input": {
      "top_k": 1,
      "top_p": 1,
      "prompt": "please describe this image.",
      "image_url": ["https://support.content.office.net/en-us/media/3dd2b79b-9160-403d-9967-af893d17b580.png"],
      "max_tokens": 45000,
      "temperature": 0.1,
      "image_base64": [],
      "system_prompt": "You are a helpful AI assistant.",
      "max_new_tokens": 458,
      "repetition_penalty": 1.1
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

The chart is a spreadsheet table with data organized into columns and rows. It includes headers labeled 'Product', 'Qtr 1', 'Qtr 2', and 'Grand Total'. There are eight products listed: Chocolade, Gummibarchen, Scottish Longbreads, Sir Rodney's Scones, Tarte au sucre, Chocolate Biscuits, and a total row at the bottom. Each product has corresponding values in the three quarters and grand total columns. For example, Chocolade has $744.60 in Qtr 1, $162.56 in Qtr 2, and a grand total of $907.16. The totals for each column are also provided at the end of the table, with Qtr 1 totaling $14,181.59, Qtr 2 totaling $8,127.78, and the Grand Total totaling $22,309.37. The table uses a green header for the first column and alternates shading between white and light grey for the rows to enhance readability.

{
  "completed_at": "2024-05-23T13:33:16.161879Z",
  "created_at": "2024-05-23T13:29:49.038000Z",
  "data_removed": false,
  "error": null,
  "id": "a2kecty0xsrgj0cfmpj91qj7v0",
  "input": {
    "top_k": 1,
    "top_p": 1,
    "prompt": "please describe this image.",
    "image_url": [
      "https://support.content.office.net/en-us/media/3dd2b79b-9160-403d-9967-af893d17b580.png"
    ],
    "max_tokens": 45000,
    "temperature": 0.1,
    "image_base64": [],
    "system_prompt": "You are a helpful AI assistant.",
    "max_new_tokens": 458,
    "repetition_penalty": 1.1
  },
  "logs": "max_tokens 45000\ntoken_count0 6\nstop_ids [1, 1]\n/root/.pyenv/versions/3.10.14/lib/python3.10/site-packages/transformers/generation/configuration_utils.py:492: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0.1` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\nwarnings.warn(\n/root/.pyenv/versions/3.10.14/lib/python3.10/site-packages/transformers/generation/configuration_utils.py:509: UserWarning: `do_sample` is set to `False`. However, `top_k` is set to `1` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `top_k`.\nwarnings.warn(",
  "metrics": {
    "predict_time": 12.318442,
    "total_time": 207.123879
  },
  "output": [
    "",
    "The ",
    "chart ",
    "is ",
    "a ",
    "",
    "spreadsheet ",
    "table ",
    "with ",
    "data ",
    "organized ",
    "into ",
    "columns ",
    "and ",
    "",
    "rows. ",
    "It ",
    "includes ",
    "headers ",
    "",
    "labeled ",
    "",
    "",
    "'Product', ",
    "",
    "",
    "'Qtr ",
    "",
    "",
    "1', ",
    "",
    "",
    "'Qtr ",
    "",
    "",
    "2', ",
    "and ",
    "",
    "",
    "'Grand ",
    "",
    "Total'. ",
    "There ",
    "are ",
    "eight ",
    "products ",
    "",
    "listed: ",
    "",
    "",
    "",
    "",
    "Chocolade, ",
    "",
    "",
    "",
    "",
    "",
    "Gummibarchen, ",
    "Scottish ",
    "",
    "",
    "",
    "",
    "Longbreads, ",
    "Sir ",
    "",
    "",
    "",
    "Rodney's ",
    "",
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    "Scones, ",
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    "Tarte ",
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    "sucre, ",
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    "Chocolate ",
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    "Biscuits, ",
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    "row ",
    "at ",
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    "",
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    "Each ",
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    "grand ",
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    "For ",
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    "$162.56 ",
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    "a ",
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    "of ",
    "",
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    "",
    "",
    "",
    "",
    "",
    "$907.16. ",
    "The ",
    "",
    "totals ",
    "for ",
    "each ",
    "column ",
    "are ",
    "also ",
    "provided ",
    "at ",
    "the ",
    "end ",
    "of ",
    "the ",
    "",
    "table, ",
    "with ",
    "",
    "Qtr ",
    "",
    "1 ",
    "",
    "totaling ",
    "",
    "",
    "",
    "",
    "",
    "",
    "",
    "",
    "",
    "",
    "$14,181.59, ",
    "",
    "Qtr ",
    "",
    "2 ",
    "",
    "totaling ",
    "",
    "",
    "",
    "",
    "",
    "",
    "",
    "",
    "",
    "$8,127.78, ",
    "and ",
    "the ",
    "Grand ",
    "Total ",
    "",
    "totaling ",
    "",
    "",
    "",
    "",
    "",
    "",
    "",
    "",
    "",
    "",
    "$22,309.37. ",
    "The ",
    "table ",
    "uses ",
    "a ",
    "green ",
    "header ",
    "for ",
    "the ",
    "first ",
    "column ",
    "and ",
    "",
    "alternates ",
    "",
    "shading ",
    "between ",
    "white ",
    "and ",
    "light ",
    "grey ",
    "for ",
    "the ",
    "rows ",
    "to ",
    "",
    "enhance ",
    "",
    "",
    "",
    "",
    "readability."
  ],
  "started_at": "2024-05-23T13:33:03.843437Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://streaming-api.svc.us.c.replicate.net/v1/streams/icoi7vsackjbx67omiskrukefpexjwscclgf2kvjiau6ktu46dda",
    "get": "https://api.replicate.com/v1/predictions/a2kecty0xsrgj0cfmpj91qj7v0",
    "cancel": "https://api.replicate.com/v1/predictions/a2kecty0xsrgj0cfmpj91qj7v0/cancel"
  },
  "version": "6afc892d5aa00e0e0883dec30f7a766fcf515c64090def9d173093ac343c2438"
}

Generated in

12.3 seconds

Tweak it Share Report

Run time and cost

This model costs approximately $0.11 to run on Replicate, or 9 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 109 seconds. The predict time for this model varies significantly based on the inputs.

Readme

test site: https://ai.zyinfo.pro/?cn=1&AI_system=phi3-v-t