Text Generation
Transformers.js
ONNX
Safetensors
gemma3_text
function-calling
prism-os
webgpu
conversational
Instructions to use AppleLampsX/prism-os-functiongemma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use AppleLampsX/prism-os-functiongemma with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-generation', 'AppleLampsX/prism-os-functiongemma');
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Download README.md from AppleLampsX/prism-os-functiongemma: direct link, hf CLI and curl.
- Browser
- Download file 1.15 kB
-
https://huggingface.co/AppleLampsX/prism-os-functiongemma/resolve/main/README.md
- Command line
-
hf download hf://AppleLampsX/prism-os-functiongemma/README.md
-
curl -L -o README.md https://huggingface.co/AppleLampsX/prism-os-functiongemma/resolve/main/README.md
1.15 kB
metadata
license: gemma
base_model: google/functiongemma-270m-it
library_name: transformers.js
tags:
- function-calling
- prism-os
- webgpu
Prism OS command center model
FunctionGemma 270M fine-tuned on the commands of
Prism OS, a desktop in the browser whose window
manager is a handwired numeric program. It turns a sentence into Prism OS's function
calls, or a short reply. It runs in the browser with Transformers.js on WebGPU
(onnx/model_q4f16.onnx, the graph of
onnx-community/functiongemma-270m-it-ONNX with these weights). The
PyTorch weights are in pytorch/.
Results on held-out phrasings
Every eval sentence uses a phrasing template that never appears in training. The checkpoint kept was the best on a separate dev set of eval sentences, which these scores leave out.
| Model | Correct |
|---|---|
| Base FunctionGemma | 108/746 |
| Fine-tuned (PyTorch, bf16) | 701/746 |
| Fine-tuned, browser build (q4f16), first 100 | 95/100 |
Use is subject to the Gemma Terms of Use.