3 models · Text utilities · Transformers.js
Text utilities in the browser
3 models handle text utilities in the browser today, from 233.9 MB (GLiNER Small v2.1) to 432.1 MB (Piiranha v1 (PII Detection)), a 413.1 MB download at the midpoint. Every one runs with Transformers.js over WebGPU or WebAssembly: no server, no install, no account.
- Models
- 3
- Smallest
- 233.9 MB
- Median
- 413.1 MB
- Largest
- 432.1 MB
Every text utilities model, ranked by WebGPU size
| Model | WebGPU download | WASM download |
|---|---|---|
| GLiNER Small v2.1 166M params | 233.9 MB q4f16 | 174.9 MB uint8 |
| Punctuate All 278.89M params | 413.1 MB q4f16 | 265.7 MB uint8 |
| Piiranha v1 (PII Detection) 278.23M params | 432.1 MB q4f16 | 302.5 MB uint8 |
Sizes measured from the HuggingFace API file tree for each model's repo, not estimated. Sorted smallest to largest by the WebGPU headline pick.
Size ladder
The WebGPU download spans 1.8x here: 233.9 MB (GLiNER Small v2.1) to 432.1 MB (Piiranha v1 (PII Detection)).
3 of 3 models (GLiNER Small v2.1, Punctuate All, Piiranha v1 (PII Detection)) download a smaller build over WebAssembly than WebGPU: the CPU-fallback quant compresses tighter than the GPU pick there.
None of the 3 models here fit under 100 MB over WebGPU.
A bytes-per-parameter comparison needs at least 3 models with a verified parameter count and a real spread between them; this group does not clear that bar yet.
Use it with Transformers.js
Every text utilities model here shares the same pipeline() task, so one snippet covers the group. This one loads GLiNER Small v2.1, the smallest download; swap the repo string for any other row in the table above.
import { pipeline } from "@huggingface/transformers";
const pipe = await pipeline("token-classification", "onnx-community/gliner_small-v2.1", {
device: "webgpu", // usually falls back to "wasm"; wrap in try/catch for production
dtype: "q4f16", // use "uint8" for the WASM build
});
const result = await pipe(/* your input */); Requires npm install @huggingface/transformers (or the CDN build).
Notable text utilities models
Other tasks
Or see every browser model grouped by task, or the main GGUF catalog for native runtimes outside the browser.
FAQ
Do all text utilities models here use the same WebGPU quant?
Yes: all 3 models here use the q4f16 WebGPU build.
What would it cost to download every text utilities model here?
1.05 GB total over WebGPU across all 3 models, if you tried every one back to back. Most projects only need the single model that fits the job, not the whole set.
Sizes measured 2026-08-01 from the HuggingFace API. Last validated 2026-09-14. See all browser models or the methodology.