Hugging Face
App · AI Models · 1 action
Run inference on open models hosted on the Hugging Face Inference API.
Query a model
Run inference on a model served by Hugging Face's serverless Inference API. Give the model's repository id and the text to send; the action returns the model's output. Works across tasks such as summarization, classification, translation, and feature extraction (embeddings).
Inputs
- Model
modeltextRequired - The Hugging Face model repository id to run, e.g. 'facebook/bart-large-cnn'. The model must be served by the hf-inference provider (Hugging Face's serverless inference) - its model page shows an 'HF Inference' provider when it is.
- Inputs
inputstextRequired - The text to send to the model - a prompt to continue, a passage to summarize or translate, a sentence to classify, and so on.
- Parameters
parametersobject - Optional task-specific parameters passed straight to the model, e.g. {"max_length": 130, "min_length": 30} for summarization. Leave empty for the model's defaults.
- Wait for model to load
wait_for_modeltrue/false - Serverless models are loaded on demand. When enabled, the request waits for a cold model to finish loading instead of failing; disable to return immediately.Default:
true.
Outputs
generated_texttext- The model's primary text output, for text-producing tasks (summarization, translation, generation). Null for tasks that don't produce text (see 'result').
modeltext- The model repository id that was queried.
result- The raw model output. Its shape depends on the model's task: a list of summaries for summarization, nested label/score lists for classification, and so on.
Example output
{
"generated_text": "Hugging Face builds tools for machine learning and hosts open models.",
"model": "facebook/bart-large-cnn",
"result": [
{
"summary_text": "Hugging Face builds tools for machine learning and hosts open models."
}
]
}