hayooucom / vision-model

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

Cold

Public
13.6K runs
L40S
GitHub
Paper
License

Run with an API

Playground API Examples README Versions

Prediction

hayooucom/vision-model:6afc892d

Model

hayooucom/vision-model:6afc892d

a2kecty0xsrgj0cfmpj91qj7v0

Status

Succeeded

Source

Web

Hardware

A40

Total duration

3m 27s

Created

11 months ago

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

{
  "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
}

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": "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 ",
    "",
    "",
    "",
    "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 ",
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    "",
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    "$744.60 ",
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    "1, ",
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    "",
    "",
    "",
    "",
    "$162.56 ",
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    "Qtr ",
    "",
    "",
    "2, ",
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    "a ",
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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

Prediction

hayooucom/vision-model:6afc892d

Model

hayooucom/vision-model:6afc892d

11axq4ccj9rgg0cfmqjsamqr8g

Status

Succeeded

Source

API

Hardware

A40

Total duration

1m 47s

Created

11 months ago

Input

top_p: 0.9
prompt: <|user|> <|image_1|> 当前时间：2024年05月23日 22:40:35 星期四这张图片有什么，请用markdown 格式展示出来。<|end|> <|assistant|>
image_url: [ "https://v.stylee.top/files/vision/upimg-1716475231541697.jpg" ]
max_tokens: 400
temperature: 0.2

{
  "top_p": 0.9,
  "prompt": "<|user|>\n<|image_1|>\n\n当前时间：2024年05月23日 22:40:35 星期四\n\n\n这张图片有什么，请用markdown 格式展示出来。<|end|>\n<|assistant|>\n\n",
  "image_url": [
    "https://v.stylee.top/files/vision/upimg-1716475231541697.jpg"
  ],
  "max_tokens": 400,
  "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 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_p: 0.9,
      prompt: "<|user|>\n<|image_1|>\n\n当前时间：2024年05月23日 22:40:35 星期四\n\n\n这张图片有什么，请用markdown 格式展示出来。<|end|>\n<|assistant|>\n\n",
      image_url: ["https://v.stylee.top/files/vision/upimg-1716475231541697.jpg"],
      max_tokens: 400,
      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 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_p": 0.9,
        "prompt": "<|user|>\n<|image_1|>\n\n当前时间：2024年05月23日 22:40:35 星期四\n\n\n这张图片有什么，请用markdown 格式展示出来。<|end|>\n<|assistant|>\n\n",
        "image_url": ["https://v.stylee.top/files/vision/upimg-1716475231541697.jpg"],
        "max_tokens": 400,
        "temperature": 0.2
    }
)

# 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": "6afc892d5aa00e0e0883dec30f7a766fcf515c64090def9d173093ac343c2438",
    "input": {
      "top_p": 0.9,
      "prompt": "<|user|>\\n<|image_1|>\\n\\n当前时间：2024年05月23日 22:40:35 星期四\\n\\n\\n这张图片有什么，请用markdown 格式展示出来。<|end|>\\n<|assistant|>\\n\\n",
      "image_url": ["https://v.stylee.top/files/vision/upimg-1716475231541697.jpg"],
      "max_tokens": 400,
      "temperature": 0.2
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

The image contains a bar chart, not a table. However, I can provide the data in a markdown table format based on the information visible in the OCR text and the image description. Here is the conversion of the bar chart data into a markdown table: ```markdown | Improvement Area | Percentage of Respondents Who Agree | |-----------------------------------------|-------------------------------------| | Having clear and pre-defined goals for meetings | 79% | | Knowing where to find the information need for a meeting | 77% | | Understanding my exact role and responsibilities when I'm invited | 76% | | Having tools to manage admin tasks like note-taking or summarization | 76% | | Having more focus time to sufficiently prepare for meetings | 75% |

{
  "completed_at": "2024-05-23T14:42:22.952753Z",
  "created_at": "2024-05-23T14:40:35.474000Z",
  "data_removed": false,
  "error": null,
  "id": "11axq4ccj9rgg0cfmqjsamqr8g",
  "input": {
    "top_p": 0.9,
    "prompt": "<|user|>\n<|image_1|>\n\n当前时间：2024年05月23日 22:40:35 星期四\n\n\n这张图片有什么，请用markdown 格式展示出来。<|end|>\n<|assistant|>\n\n",
    "image_url": [
      "https://v.stylee.top/files/vision/upimg-1716475231541697.jpg"
    ],
    "max_tokens": 400,
    "temperature": 0.2
  },
  "logs": "max_tokens 400\ntoken_count0 71\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 `0.2` -- 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:497: UserWarning: `do_sample` is set to `False`. However, `top_p` is set to `0.9` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `top_p`.\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": 10.717024,
    "total_time": 107.478753
  },
  "output": [
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    "image ",
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    "",
    "chart, ",
    "not ",
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    "",
    "table. ",
    "",
    "However, ",
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    "a ",
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    "```markdown\n",
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    "| ",
    "",
    "",
    "Percentage ",
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    "|\n",
    "",
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    "",
    "",
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    "|-----------------------------------------|-------------------------------------|\n",
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    "76%                ",
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    "|\n",
    "",
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    "| ",
    "",
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    "",
    "76%                ",
    "              ",
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    "|\n",
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    "meetings ",
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    "",
    "",
    "",
    "75%                ",
    "              ",
    " ",
    "|\n",
    ""
  ],
  "started_at": "2024-05-23T14:42:12.235729Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/11axq4ccj9rgg0cfmqjsamqr8g",
    "cancel": "https://api.replicate.com/v1/predictions/11axq4ccj9rgg0cfmqjsamqr8g/cancel"
  },
  "version": "6afc892d5aa00e0e0883dec30f7a766fcf515c64090def9d173093ac343c2438"
}

Generated in

10.7 seconds

Tweak it Share Report

Want to make some of these yourself?

Run this model

hayooucom / vision-model

Prediction

Input

Output

Prediction

Input

Output

Logs (a2kecty0xsrgj0cfmpj91qj7v0)

Logs (11axq4ccj9rgg0cfmqjsamqr8g)