ActionHugging FaceUpdated September 2026
How do I classify text with Hugging Face?
Short answer: You can hf text classification in Hugging Face by hand from its own interface, but it won’t repeat itself. On TinyCommand, add the Hugging Face HF Text Classification action to a workflow, map its 2 inputs from any upstream app, and it runs automatically every time the trigger fires. No code, and a free tier to start.
Inputs
The fields this action accepts.
Every field can be mapped from an upstream trigger, AI step, table row, or hard-coded literal.
| Field | Type | Required | Description |
|---|---|---|---|
Model model | string | Required | HF model id |
Text text | string | Required | Text (required) |
Sample request
{"model": "e.g. cardiffnlp/twitter-roberta-base-sentiment-latest","text": "{{trigger.text}}"}
Returns
[[{"label": "POSITIVE","score": 0.99}]]
Use these fields in downstream nodes for routing, logging, or error handling.
Triggered by
Apps that pair well as the trigger for HF Text Classification.
Any of these apps can fire this action as part of a workflow.
FAQ
Questions about HF Text Classification.
What does the HF Text Classification action do in Hugging Face?
Runs any classifier model from HF Hub on text input — sentiment, toxicity, NER, intent. Pick the right classifier for your use case from the broad Hub catalog.
What inputs does HF Text Classification require?
Required: Model, Text. Every input accepts a static value or a variable from any upstream node in your workflow.
Can I use dynamic inputs from earlier workflow nodes?
Yes. Any field on this action can pull values from upstream nodes, whether that's a form response, a trigger payload, an AI output, or a lookup result.
What happens if Hugging Face returns an error?
The run history shows the failed step with its input and the error message Hugging Face returned, so you can fix the input and run the workflow again. Automatic retries are built into HTTP steps only, where you can also set your own retry count and delay.
Does HF Text Classification support batch operations?
Run HF Text Classification inside a loop to process each item in an array. TinyCommand does not throttle calls for you, so for large arrays add a Delay step if you need to stay within Hugging Face's rate limits.
More actions
Other Hugging Face actions.
Action
Hugging Face Chat Completion
Runs chat completion against any text-generation model on Hugging Face Hub that supports the TGI server. OpenAI-compatible message-array shape. Model selection via model ID (e.g., meta-llama/Llama-3.3-70B-Instruct).
ActionHF Feature Extraction (Embeddings)
Generates sentence embeddings from any sentence-transformers or BGE-class model on the HF Hub. For RAG-pipeline vector generation when you want a specific HF-hosted embedding model.
ActionHF Text to Image
Generates images from text using any HF-hosted image model (SDXL, SD3.5, Flux variants, community fine-tunes). For accessing niche or specific image models from the broad HF catalog.