This documentation describes the integration of MindsDB with Hugging Face Inference API. The integration allows for the deployment of Hugging Face models through Inference API within MindsDB, providing the models with access to data from various data sources.


Before proceeding, ensure the following prerequisites are met:

  1. Install MindsDB locally via Docker or use MindsDB Cloud.
  2. To use Hugging Face Inference API within MindsDB, install the required dependencies following this instruction.
  3. Obtain the API key for Hugging Face Inference API required to deploy and use Hugging Face models through Inference API within MindsDB. Generate tokens in the Settings -> Access Tokens tab of the Hugging Face account.


Create an AI engine from the Hugging Face Inference API handler.

CREATE ML_ENGINE huggingface_api_engine
FROM huggingface_api
      huggingface_api_api_key = 'api-key-value';

Create a model using huggingface_api_engine as an engine.

CREATE MODEL huggingface_api_model
PREDICT target_column
      engine = 'huggingface_api_engine',     -- engine name as created via CREATE ML_ENGINE
      task = 'task_name',                -- choose one of 'text-classification', 'text-generation', 'question-answering', 'sentence-similarity', 'zero-shot-classification', 'summarization', 'fill-mask', 'image-classification', 'object-detection', 'automatic-speech-recognition', 'audio-classification'
      input_column = 'column_name',      -- column that stores input/question to the model
      labels = ['label 1', 'label 2'];   -- labels used to classify data (used for classification tasks)


The following usage examples utilize huggingface_api_engine to create a model with the CREATE MODEL statement.

Create a model to classify input text as spam or ham.

CREATE MODEL spam_classifier
PREDICT is_spam
      engine = 'huggingface_api_engine',
      task = 'text-classification',
      column = 'text';

Query the model to get predictions.

SELECT text, is_spam
FROM spam_classifier
WHERE text = 'Subscribe to this channel asap';

Here is the output:

| text                           | is_spam |
| Subscribe to this channel asap | spam    |

Next Steps

Follow this link to see more use case examples.