---
title: cali
emoji: 🌏
colorFrom: blue
colorTo: indigo
sdk: gradio
sdk_version: 6.30.0
app_file: app.py
python_version: "3.12"
short_description: Indonesian-English translation and CALI text generation
license: apache-2.0
models:
  - Sandroeth/cali-id-en-translate
  - Sandroeth/cali-0.1B
---

# cali

Explore two lightweight language models by Sandroeth in an English-language interface.

- **Translation:** translate everyday sentences between Indonesian and English.
- **Explore CALI:** continue a text prompt with the experimental CALI-0.1B base model.

## Inference

Translation follows the [official model README](https://huggingface.co/Sandroeth/cali-id-en-translate/blob/main/README.md): `[id→en]\n{text}\n→` or `[en→id]\n{text}\n→`, deterministic decoding, `repetition_penalty=1.5`, `no_repeat_ngram_size=3`, `use_cache=False`, and 64 output tokens by default. The first-sentence option matches the official example; disable it to inspect the complete generated output.

The base model receives a plain text prompt without a chat template. Both models use their custom architecture code at the revisions pinned in `app.py`. Float32 preserves compatibility with the translation model's RoPE implementation. Transformers 5.9.0 matches the translation checkpoint configuration.

The combined input and output budget is 1024 tokens, with up to 256 output tokens. Translation inputs are limited to 200 words.

## Hosting and API

This Gradio Space uses ZeroGPU. Both models are loaded once at startup, and the inference handlers use `@spaces.GPU`. CPU execution is also supported when available. Spaces manages Gradio, PyTorch, `spaces`, and `huggingface_hub`.

Gradio API endpoints: `/translate` and `/complete`. MCP is enabled. Examples are cached lazily after first use. Each response includes token counts and inference time.

## Limitations

Translation works best on everyday sentences. Very short inputs, technical topics, and long passages may be unreliable. CALI-0.1B is an experimental base model trained on limited data; continuations can repeat, drift off-topic, or be inconsistent.

Both models are released under Apache 2.0 by Sandroeth.