morphoformer 3.0.1

MorphFormer: multilingual morphological reinflection via character-level Transformer

MorphFormer v3

Character-level Transformer for multilingual morphological reinflection.

Installation

pip install morphoformer

Requires Python >= 3.14 and PyTorch >= 2.0.

Dependencies (chartoken, torchblocks, sigmorphon, trainkit) are installed automatically.

Quick Start

# Download data
morphoformer download --lang rus,deu,fra --merge

# Train
morphoformer train --preset medium --data "data/collections/*_train.tsv" --device cuda

# Infer
morphoformer infer --checkpoint checkpoints/morphformer_epoch50.pt --word "laufen" --morph "V;IND;PST;3;SG" --lang deu

# Interactive REPL
morphoformer serve --checkpoint checkpoints/morphformer_epoch50.pt

Presets

Preset	d_model	Encoder	Decoder	~Params	VRAM
small	384	4 layers	3 layers	~7M	< 4 GB
medium	512	8 layers	6 layers	~45M	4-8 GB
large	768	10 layers	8 layers	~120M	>= 8 GB

CLI Commands

Command	Description
train	Train model from TSV data
infer	Single-word inference
serve	Interactive REPL
download	Download SigMorphon datasets
modules	List registered NN modules
init-config	Generate TOML config template

Data Format

TSV with columns: lemma\tfeatures\tsurface_form\tlanguage

laufen	V;IND;PST;3;SG	lief	deu

Python API

import torch
from chartoken import CharVocab, FeatureVocab
from morphoformer.model import MorphFormer
from morphoformer.inference import greedy_decode

checkpoint = torch.load("checkpoints/morphformer_epoch50.pt", map_location="cpu", weights_only=False)
char_vocab = CharVocab.from_dict(checkpoint["char_vocab"])
feature_vocab = FeatureVocab.from_dict(checkpoint["feature_vocab"])
lang_to_id = checkpoint["lang_to_id"]

# ... build model, load state_dict, call greedy_decode()

Architecture

• Encoder-Decoder Transformer at character level
• Grouped Query Attention (GQA) with KV cache
• RoPE positional embeddings
• SwiGLU feed-forward networks
• Language-conditioned adapters
• Conformer-style local convolution in encoder
• Structured morphological feature encoding

Supported Devices

Device	Flag
Auto-detect	--device auto
NVIDIA GPU	--device cuda
AMD GPU	--device rocm
Intel Arc	--device xpu
Apple Silicon	--device mps
CPU	--device cpu

License

See LICENSE file in the repository root.