Prediction

ID

y7wat0g5qdrma0cktb9a72gft8

Status

Succeeded

Source

Web

Hardware

L40S

Total duration

18.1s

Created

5 months ago

Input

image
top_p: 0.95
prompt: Which era does this piece belong to? Give details about the era.
max_tokens: 512
temperature: 0.7

{
  "image": "https://replicate.delivery/pbxt/M9qbwdt9ifXXUqlD0ZetwzYSEnweBWWr2GKEceTlcE5oGWmq/rococo.jpg",
  "top_p": 0.95,
  "prompt": "Which era does this piece belong to? Give details about the era.",
  "max_tokens": 512,
  "temperature": 0.7
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run lucataco/ollama-llama3.2-vision-11b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/ollama-llama3.2-vision-11b:d4e81fc1472556464f1ee5cea4de177b2fe95a6eaadb5f63335df1ba654597af",
  {
    input: {
      image: "https://replicate.delivery/pbxt/M9qbwdt9ifXXUqlD0ZetwzYSEnweBWWr2GKEceTlcE5oGWmq/rococo.jpg",
      top_p: 0.95,
      prompt: "Which era does this piece belong to? Give details about the era.",
      max_tokens: 512,
      temperature: 0.7
    }
  }
);

console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

pip install replicate

Import the client:

import replicate

Run lucataco/ollama-llama3.2-vision-11b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/ollama-llama3.2-vision-11b:d4e81fc1472556464f1ee5cea4de177b2fe95a6eaadb5f63335df1ba654597af",
    input={
        "image": "https://replicate.delivery/pbxt/M9qbwdt9ifXXUqlD0ZetwzYSEnweBWWr2GKEceTlcE5oGWmq/rococo.jpg",
        "top_p": 0.95,
        "prompt": "Which era does this piece belong to? Give details about the era.",
        "max_tokens": 512,
        "temperature": 0.7
    }
)

# The lucataco/ollama-llama3.2-vision-11b 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/lucataco/ollama-llama3.2-vision-11b/api#output-schema
    print(item, end="")

To learn more, take a look at the guide on getting started with Python.

Run lucataco/ollama-llama3.2-vision-11b 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": "lucataco/ollama-llama3.2-vision-11b:d4e81fc1472556464f1ee5cea4de177b2fe95a6eaadb5f63335df1ba654597af",
    "input": {
      "image": "https://replicate.delivery/pbxt/M9qbwdt9ifXXUqlD0ZetwzYSEnweBWWr2GKEceTlcE5oGWmq/rococo.jpg",
      "top_p": 0.95,
      "prompt": "Which era does this piece belong to? Give details about the era.",
      "max_tokens": 512,
      "temperature": 0.7
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

The painting appears to be from the Rococo period, which was a style that emerged in Europe around the early 18th century and lasted until the late 18th century. **Characteristics of the Rococo Period** • Characterized by light, airy, and delicate designs • Often featured pastel colors, flowers, and foliage • Ornate decorations, such as intricate carvings and gilded details **A Focus on Sensuality and Playfulness** The painting's playful and sensual depiction of the women suggests a focus on pleasure and enjoyment, which was a key aspect of the Rococo style. The use of pastel colors and floral motifs adds to the overall sense of lightheartedness and joy. **Rococo Influence in Art and Architecture** The Rococo period had a significant influence on art and architecture during this time. It was particularly popular in France, where it was known as "le style rocaille." The style was characterized by its use of curved lines, asymmetrical compositions, and playful decorations. **A Beautiful Example of Rococo Art** Overall, the painting is a beautiful example of Rococo art, showcasing the era's focus on beauty, pleasure, and sensuality.

{
  "completed_at": "2024-12-17T04:13:37.773277Z",
  "created_at": "2024-12-17T04:13:19.675000Z",
  "data_removed": false,
  "error": null,
  "id": "y7wat0g5qdrma0cktb9a72gft8",
  "input": {
    "image": "https://replicate.delivery/pbxt/M9qbwdt9ifXXUqlD0ZetwzYSEnweBWWr2GKEceTlcE5oGWmq/rococo.jpg",
    "top_p": 0.95,
    "prompt": "Which era does this piece belong to? Give details about the era.",
    "max_tokens": 512,
    "temperature": 0.7
  },
  "logs": null,
  "metrics": {
    "predict_time": 5.939746479,
    "total_time": 18.098277
  },
  "output": [
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  ],
  "started_at": "2024-12-17T04:13:31.833530Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://stream-b.svc.ric1.c.replicate.net/v1/streams/2wioabwqrkwwix5rt3qgdfwddmnofhscynr7zz5flkelqz5pfuxa",
    "get": "https://api.replicate.com/v1/predictions/y7wat0g5qdrma0cktb9a72gft8",
    "cancel": "https://api.replicate.com/v1/predictions/y7wat0g5qdrma0cktb9a72gft8/cancel"
  },
  "version": "d4e81fc1472556464f1ee5cea4de177b2fe95a6eaadb5f63335df1ba654597af"
}

Generated in

5.9 seconds

lucataco/ollama-llama3.2-vision-11b:d4e81fc1472556464f1ee5cea4de177b2fe95a6eaadb5f63335df1ba654597af

Prediction

Model

ID

cedwe3vqc1rm80cktb994kxhq8

Status

Succeeded

Source

Web

Hardware

L40S

Total duration

2.4s

Created

5 months ago

Input

image
top_p: 0.95
prompt: Where do the droughts happen according to this diagram?
max_tokens: 512
temperature: 0.7

{
  "image": "https://replicate.delivery/pbxt/M9qcP9sd5keEDnMPLvsc1Yv0hm3JUg6e7qlZcpBwFOUfMKLQ/weather_events.png",
  "top_p": 0.95,
  "prompt": "Where do the droughts happen according to this diagram?",
  "max_tokens": 512,
  "temperature": 0.7
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run lucataco/ollama-llama3.2-vision-11b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/ollama-llama3.2-vision-11b:d4e81fc1472556464f1ee5cea4de177b2fe95a6eaadb5f63335df1ba654597af",
  {
    input: {
      image: "https://replicate.delivery/pbxt/M9qcP9sd5keEDnMPLvsc1Yv0hm3JUg6e7qlZcpBwFOUfMKLQ/weather_events.png",
      top_p: 0.95,
      prompt: "Where do the droughts happen according to this diagram?",
      max_tokens: 512,
      temperature: 0.7
    }
  }
);

console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

pip install replicate

Import the client:

import replicate

Run lucataco/ollama-llama3.2-vision-11b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/ollama-llama3.2-vision-11b:d4e81fc1472556464f1ee5cea4de177b2fe95a6eaadb5f63335df1ba654597af",
    input={
        "image": "https://replicate.delivery/pbxt/M9qcP9sd5keEDnMPLvsc1Yv0hm3JUg6e7qlZcpBwFOUfMKLQ/weather_events.png",
        "top_p": 0.95,
        "prompt": "Where do the droughts happen according to this diagram?",
        "max_tokens": 512,
        "temperature": 0.7
    }
)

# The lucataco/ollama-llama3.2-vision-11b 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/lucataco/ollama-llama3.2-vision-11b/api#output-schema
    print(item, end="")

To learn more, take a look at the guide on getting started with Python.

Run lucataco/ollama-llama3.2-vision-11b 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": "lucataco/ollama-llama3.2-vision-11b:d4e81fc1472556464f1ee5cea4de177b2fe95a6eaadb5f63335df1ba654597af",
    "input": {
      "image": "https://replicate.delivery/pbxt/M9qcP9sd5keEDnMPLvsc1Yv0hm3JUg6e7qlZcpBwFOUfMKLQ/weather_events.png",
      "top_p": 0.95,
      "prompt": "Where do the droughts happen according to this diagram?",
      "max_tokens": 512,
      "temperature": 0.7
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

According to the diagram, severe droughts occurred in eastern and southern Africa. The specific countries mentioned are not provided on the diagram, but it is implied that these locations experienced significant water shortages during 2016.

Generated in

2.4 seconds

lucataco/ollama-llama3.2-vision-11b:d4e81fc1472556464f1ee5cea4de177b2fe95a6eaadb5f63335df1ba654597af

Prediction

Model

ID

sfnwfw5gzxrm80cktb9bwq1kt4

Status

Succeeded

Source

Web

Hardware

L40S

Total duration

2.7s

Created

5 months ago

Input

image
top_p: 0.95
prompt: What happens when you take out white cat from this chain?
max_tokens: 512
temperature: 0.7

{
  "image": "https://replicate.delivery/pbxt/M9qceG4RL6Ov5dpJwPv76d6L1UoNtMAfoGq9OgN6dkp4IJJf/ai2d_test.jpg",
  "top_p": 0.95,
  "prompt": "What happens when you take out white cat from this chain?",
  "max_tokens": 512,
  "temperature": 0.7
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run lucataco/ollama-llama3.2-vision-11b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/ollama-llama3.2-vision-11b:d4e81fc1472556464f1ee5cea4de177b2fe95a6eaadb5f63335df1ba654597af",
  {
    input: {
      image: "https://replicate.delivery/pbxt/M9qceG4RL6Ov5dpJwPv76d6L1UoNtMAfoGq9OgN6dkp4IJJf/ai2d_test.jpg",
      top_p: 0.95,
      prompt: "What happens when you take out white cat from this chain?",
      max_tokens: 512,
      temperature: 0.7
    }
  }
);

console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

pip install replicate

Import the client:

import replicate

Run lucataco/ollama-llama3.2-vision-11b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/ollama-llama3.2-vision-11b:d4e81fc1472556464f1ee5cea4de177b2fe95a6eaadb5f63335df1ba654597af",
    input={
        "image": "https://replicate.delivery/pbxt/M9qceG4RL6Ov5dpJwPv76d6L1UoNtMAfoGq9OgN6dkp4IJJf/ai2d_test.jpg",
        "top_p": 0.95,
        "prompt": "What happens when you take out white cat from this chain?",
        "max_tokens": 512,
        "temperature": 0.7
    }
)

# The lucataco/ollama-llama3.2-vision-11b 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/lucataco/ollama-llama3.2-vision-11b/api#output-schema
    print(item, end="")

To learn more, take a look at the guide on getting started with Python.

Run lucataco/ollama-llama3.2-vision-11b 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": "lucataco/ollama-llama3.2-vision-11b:d4e81fc1472556464f1ee5cea4de177b2fe95a6eaadb5f63335df1ba654597af",
    "input": {
      "image": "https://replicate.delivery/pbxt/M9qceG4RL6Ov5dpJwPv76d6L1UoNtMAfoGq9OgN6dkp4IJJf/ai2d_test.jpg",
      "top_p": 0.95,
      "prompt": "What happens when you take out white cat from this chain?",
      "max_tokens": 512,
      "temperature": 0.7
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

The white cat is not present in the food web. The correct term for a wild animal would be "wildcat." If we were to remove a wildcat from the ecosystem, it would no longer be able to hunt or prey on other animals. This could have cascading effects throughout the entire ecosystem. *Answer*: Wildcat will lose its source of food and nutrients

Generated in

2.7 seconds

lucataco/ollama-llama3.2-vision-11b:d4e81fc1472556464f1ee5cea4de177b2fe95a6eaadb5f63335df1ba654597af

Prediction

Model

ID

f5k4rhfw7xrmc0cktb9aywvrf8

Status

Succeeded

Source

Web

Hardware

L40S

Total duration

2.7s

Created

5 months ago

Input

image
top_p: 0.95
prompt: How long does it take from invoice date to due date? Be short and concise.
max_tokens: 512
temperature: 0.7

{
  "image": "https://replicate.delivery/pbxt/M9qcwNcnvBaN9N0vMmHSiXij24PPaE23uAmHjzu2wnUWssmn/invoice.png",
  "top_p": 0.95,
  "prompt": "How long does it take from invoice date to due date? Be short and concise.",
  "max_tokens": 512,
  "temperature": 0.7
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run lucataco/ollama-llama3.2-vision-11b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/ollama-llama3.2-vision-11b:d4e81fc1472556464f1ee5cea4de177b2fe95a6eaadb5f63335df1ba654597af",
  {
    input: {
      image: "https://replicate.delivery/pbxt/M9qcwNcnvBaN9N0vMmHSiXij24PPaE23uAmHjzu2wnUWssmn/invoice.png",
      top_p: 0.95,
      prompt: "How long does it take from invoice date to due date? Be short and concise.",
      max_tokens: 512,
      temperature: 0.7
    }
  }
);

console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

pip install replicate

Import the client:

import replicate

Run lucataco/ollama-llama3.2-vision-11b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/ollama-llama3.2-vision-11b:d4e81fc1472556464f1ee5cea4de177b2fe95a6eaadb5f63335df1ba654597af",
    input={
        "image": "https://replicate.delivery/pbxt/M9qcwNcnvBaN9N0vMmHSiXij24PPaE23uAmHjzu2wnUWssmn/invoice.png",
        "top_p": 0.95,
        "prompt": "How long does it take from invoice date to due date? Be short and concise.",
        "max_tokens": 512,
        "temperature": 0.7
    }
)

# The lucataco/ollama-llama3.2-vision-11b 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/lucataco/ollama-llama3.2-vision-11b/api#output-schema
    print(item, end="")

To learn more, take a look at the guide on getting started with Python.

Run lucataco/ollama-llama3.2-vision-11b 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": "lucataco/ollama-llama3.2-vision-11b:d4e81fc1472556464f1ee5cea4de177b2fe95a6eaadb5f63335df1ba654597af",
    "input": {
      "image": "https://replicate.delivery/pbxt/M9qcwNcnvBaN9N0vMmHSiXij24PPaE23uAmHjzu2wnUWssmn/invoice.png",
      "top_p": 0.95,
      "prompt": "How long does it take from invoice date to due date? Be short and concise.",
      "max_tokens": 512,
      "temperature": 0.7
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

From the invoice date of 11/02/2019 to the due date of 26/02/2019, there is a difference of **15 days**. This calculation was performed by subtracting the invoice date from the due date: 26/02/2019 - 11/02/2019 = 15

Generated in

2.7 seconds

lucataco/ollama-llama3.2-vision-11b:d4e81fc1472556464f1ee5cea4de177b2fe95a6eaadb5f63335df1ba654597af

Prediction

Model

ID

qkz5d42t2drmc0cktb9vwddzc8

Status

Succeeded

Source

Web

Hardware

L40S

Total duration

5.1s

Created

5 months ago

Input

image
top_p: 0.95
prompt: Where to find this monument? Can you give me other recommendations around the area?
max_tokens: 512
temperature: 0.7

{
  "image": "https://replicate.delivery/pbxt/M9qdJvwf7CzKHmBNCOxLEu3KtrN5PhdaZEbyOyD77iAYm8kq/wat_arun.jpg",
  "top_p": 0.95,
  "prompt": "Where to find this monument? Can you give me other recommendations around the area?",
  "max_tokens": 512,
  "temperature": 0.7
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run lucataco/ollama-llama3.2-vision-11b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/ollama-llama3.2-vision-11b:d4e81fc1472556464f1ee5cea4de177b2fe95a6eaadb5f63335df1ba654597af",
  {
    input: {
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      top_p: 0.95,
      prompt: "Where to find this monument? Can you give me other recommendations around the area?",
      max_tokens: 512,
      temperature: 0.7
    }
  }
);

console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

pip install replicate

Import the client:

import replicate

Run lucataco/ollama-llama3.2-vision-11b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/ollama-llama3.2-vision-11b:d4e81fc1472556464f1ee5cea4de177b2fe95a6eaadb5f63335df1ba654597af",
    input={
        "image": "https://replicate.delivery/pbxt/M9qdJvwf7CzKHmBNCOxLEu3KtrN5PhdaZEbyOyD77iAYm8kq/wat_arun.jpg",
        "top_p": 0.95,
        "prompt": "Where to find this monument? Can you give me other recommendations around the area?",
        "max_tokens": 512,
        "temperature": 0.7
    }
)

# The lucataco/ollama-llama3.2-vision-11b 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/lucataco/ollama-llama3.2-vision-11b/api#output-schema
    print(item, end="")

To learn more, take a look at the guide on getting started with Python.

Run lucataco/ollama-llama3.2-vision-11b 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": "lucataco/ollama-llama3.2-vision-11b:d4e81fc1472556464f1ee5cea4de177b2fe95a6eaadb5f63335df1ba654597af",
    "input": {
      "image": "https://replicate.delivery/pbxt/M9qdJvwf7CzKHmBNCOxLEu3KtrN5PhdaZEbyOyD77iAYm8kq/wat_arun.jpg",
      "top_p": 0.95,
      "prompt": "Where to find this monument? Can you give me other recommendations around the area?",
      "max_tokens": 512,
      "temperature": 0.7
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

**Wat Phra Kaew (Temple of the Emerald Buddha)** in Bangkok, Thailand. Located within the Grand Palace complex, Wat Phra Kaew is a highly revered and sacred site that houses the iconic Emerald Buddha image. The temple's design incorporates traditional Thai architecture with intricate details and ornate decorations, featuring an imposing spire topped by a golden finial adorned with images of mythical creatures. **Recommendations for Your Visit:** * **Grand Palace**: Explore the sprawling palace grounds, which include several other notable temples and buildings. * **Wat Arun (Temple of Dawn)**: A nearby temple famous for its distinctive spire covered in colorful ceramics and glints of gold. * **Chao Phraya River Cruise**: Take a boat ride along the river to admire the city's skyline and learn about its history. * **Jim Thompson House Museum**: Visit this museum dedicated to Thai art and culture, featuring traditional architecture and beautiful gardens. Wat Phra Kaew is an absolute must-visit attraction when in Bangkok. With these recommendations, you'll have a well-rounded experience of the city's rich cultural heritage.

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    "top_p": 0.95,
    "prompt": "Where to find this monument? Can you give me other recommendations around the area?",
    "max_tokens": 512,
    "temperature": 0.7
  },
  "logs": null,
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    "get": "https://api.replicate.com/v1/predictions/qkz5d42t2drmc0cktb9vwddzc8",
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}

Generated in

5.1 seconds