| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: intent_model |
| results: [] |
| language: |
| - en |
| --- |
| # prompt-intent-mini |
|
|
| **A lightweight model for classifying the intent behind a prompt.** |
| Built by [TinyModels](https://huggingface.co/TinyModels) — small footprint, serious performance. |
|
|
| --- |
|
|
| ## What it does |
|
|
| `prompt-intent-mini` takes a user prompt as input and returns its intent label — what the user is *actually trying to do* with that prompt. Whether it's a question, a command, a creative request, or something else entirely, the model picks it up fast and with minimal compute. |
|
|
| This is useful anywhere you need to route, filter, or understand prompts before passing them downstream — chatbots, pipelines, safety layers, you name it. |
|
|
| --- |
|
|
| ## Quick Start |
|
|
| ```python |
| from transformers import pipeline |
| |
| classifier = pipeline("text-classification", model="TinyModels/prompt-intent-mini") |
| |
| result = classifier("Write me a poem about the ocean") |
| print(result) |
| # [{'label': 'creative_generation', 'score': 0.97}] |
| ``` |
|
|
| --- |
|
|
| ## Model Details |
|
|
| | Property | Value | |
| |---|---| |
| | **Model type** | Text classification | |
| | **Base architecture** | Transformer (encoder) | |
| | **Task** | Prompt intent classification | |
| | **Size** | Tiny / <50M params | |
| | **Framework** | PyTorch + 🤗 Transformers | |
| | **Organization** | [TinyModels](https://huggingface.co/TinyModels) | |
|
|
| --- |
|
|
| ## Why we built this |
|
|
| Most intent classifiers are either too big to run cheaply or too narrow to generalize. We wanted something that sits at the front of a pipeline and just *works* — fast inference, low memory, no GPU required for most use cases. |
|
|
| `prompt-intent-mini` follows the same principle as everything we ship at TinyModels: it does one job well, fits anywhere, and doesn't cost you a GPU bill to run. |
|
|
| --- |
|
|
| ## Installation |
|
|
| ```bash |
| pip install transformers torch |
| ``` |
|
|
| --- |
|
|
| ## Intended Use |
|
|
| - Prompt routing in LLM pipelines |
| - Intent-aware moderation or filtering |
| - Chatbot understanding layers |
| - Any application that needs to know *what a user wants* before acting on it |
|
|
| --- |
|
|
| ## Limitations |
|
|
| - Trained on English prompts. Other languages may see reduced accuracy. |
| - Edge cases with highly ambiguous or mixed-intent prompts may not classify cleanly. |
| - This is a `mini` model — for more complex, multi-label scenarios, a larger variant may be more appropriate. |
|
|
| --- |
|
|
| ## Part of the TinyModels family |
|
|
| This model was created by [TinyModels](https://huggingface.co/TinyModels), a community building small, fast, open models that anyone can run. No paywalls. No gatekeeping. |
|
|
| > *Tiny models. Huge ambitions.* |
