92 lines
2.0 KiB
Markdown
92 lines
2.0 KiB
Markdown
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# Prompt-to-NFT Container
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## Overview
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## Building & Running the Container in Isolation
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Note that this container is meant to be started by the infernet-node. For development &
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Testing purposes, you can run the container in isolation using the following commands.
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### Building the Container
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Simply run the following command to build the container.
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```bash
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make build
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```
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Consult the [Makefile](./Makefile) for the build command.
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### Adding Arweave File
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Add your arweave wallet file
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### Running the Container
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To run the container, you can use the following command:
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```bash
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make run
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```
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## Testing the Container
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Run the following command to run an inference:
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```bash
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curl -X POST http://127.0.0.1:3000/service_output \
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-H "Content-Type: application/json" \
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-d '{"source":1, "data": {"prompt": "a golden retriever skiing"}}'
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```
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#### Note Regarding the Input
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The inputs provided above correspond to an iris flower with the following
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characteristics. Refer to the
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1. Sepal Length: `5.5cm`
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2. Sepal Width: `2.4cm`
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3. Petal Length: `3.8cm`
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4. Petal Width: `1.1cm`
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Putting this input into a vector and scaling it, we get the following scaled input:
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```python
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[1.0380048, 0.5586108, 1.1037828, 1.712096]
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```
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Refer
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to [this function in the model's repository](https://github.com/ritual-net/simple-ml-models/blob/03ebc6fb15d33efe20b7782505b1a65ce3975222/iris_classification/iris_inference_pytorch.py#L13)
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for more information on how the input is scaled.
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For more context on the Iris dataset, refer to
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the [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/datasets/iris).
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### Output
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By running the above command, you should get a response similar to the following:
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```json
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[
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[
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[
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0.0010151526657864451,
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0.014391022734344006,
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0.9845937490463257
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]
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]
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]
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```
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The response corresponds to the model's prediction for each of the classes:
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```python
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['setosa', 'versicolor', 'virginica']
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```
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In this case, the model predicts that the input corresponds to the class `virginica`with
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a probability of `0.9845937490463257`(~98.5%).
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