README.md

---
license: other
license_name: lfm1.0
license_link: LICENSE
base_model: LiquidAI/LFM2.5-Encoder-350M-Spellchecker
pipeline_tag: token-classification
library_name: litert
tags:
- litert
- tflite
- on-device
- edge
- encoder
- spellcheck
- grammar
- gec
- liquid
- lfm2
- lfm2.5
---

# LFM2.5-Encoder-350M-Spellchecker — LiteRT

[LiquidAI/LFM2.5-Encoder-350M-Spellchecker](https://huggingface.co/LiquidAI/LFM2.5-Encoder-350M-Spellchecker) converted to **LiteRT** (`.tflite`) for on-device inference. A GECToR-style two-head tagger that corrects misspellings and grammar token by token, fully offline ([demo Space](https://huggingface.co/spaces/LiquidAI/spellchecker)).

| File | Recipe | Size | |
|---|---|---|---|
| `LFM2.5-Encoder-350M-Spellchecker_wi8fc.tflite` | int8 dynamic-range (linears + embedding + tied vocab heads, convs float) | 429 MB | mobile + desktop (iPhone-verified bit-exact, 64 ms) |
| `LFM2.5-Encoder-350M-Spellchecker_fp16.tflite` | fp16 weights, float compute | 847 MB | desktop — phone memory limits (XNNPACK per-signature fp32 unpacking) |

## Signature

`gec_128` (S = 128, batch 1, right-padded; the base model's own decode uses max_len 128): `input_ids` int32 `[1, 128]` (**prepend the tokenizer BOS as the sentence anchor**), `attention_mask` int32 `[1, 128]` → two outputs, both zeroed at padded positions:

| Output | Shape | Meaning |
|---|---|---|
| `label_logits` | float32 `[1, 128, 128802]` | per-token edit tag: 0 `$KEEP`, 1 `$DELETE`, `2..2+V` `$REPLACE_<piece>`, `2+V..` `$APPEND_<piece>` (V = 64400 BPE pieces) |
| `detect_logits` | float32 `[1, 128, 2]` | P(token is part of an error) gate |

Host-side decode is the base repo's algorithm: argmax the tags, gate by `softmax(detect)[1] >= min_error_prob`, apply the edits, and iterate (≤3 passes) until the text stops changing. The base repo also bundles an optional PyTorch **reranker** for its published maximum-precision operating point — that stays host-side/desktop; this artifact covers the tagger (a fully supported mode of the base model's `.correct()`).

## Verification

Task-level parity vs the PyTorch reference ("She go to school every day ." → single `$REPLACE` on "go"): fp32, fp16 and int8 all produce the **identical edit** (same position, same replacement piece, detect head agreeing). On an iPhone 17 Pro the int8 file reproduces the desktop outputs **bit-exactly on both heads** — including the full `[1, 128, 128802]` label tensor — (cosine 1.000000, max diff 0.0) at 64 ms per pass (6 threads, XNNPACK).

## License

LFM Open License v1.0 (see `LICENSE`, unchanged from the base model). Note the license's commercial-use threshold (Section 5). This repository redistributes converted **Derivative Works** of LiquidAI/LFM2.5-Encoder-350M-Spellchecker with modification notices per Section 4; all credit for the model to [Liquid AI](https://www.liquid.ai/).