---
language:
  - en
license: mit
base_model: microsoft/deberta-v3-xsmall
pipeline_tag: token-classification
tags:
  - dependency-parsing
  - pos-tagging
  - universal-dependencies
datasets:
  - universal_dependencies
metrics:
  - accuracy
  - las
  - uas
model-index:
  - name: deberta-v3-xsmall-biaffine-dep-pos-en-ewt-gum
    results:
      - task:
          type: token-classification
          name: Dependency Parsing & POS/Morphology Tagging
        dataset:
          type: universal_dependencies
          name: EWT + GUM
          split: test
        metrics:
          - type: las
            name: LAS
            value: 92.97
          - type: uas
            name: UAS
            value: 94.74
          - type: accuracy
            name: UPOS
            value: 98.04
          - type: ucm
            name: UCM
            value: 70.23
          - type: lcm
            name: LCM
            value: 60.91
---

# ModernBiaffineParser — microsoft/deberta-v3-xsmall

Biaffine dependency parser + joint UPOS tagger trained on
[Universal Dependencies English Web Treebank (EWT)](https://universaldependencies.org/treebanks/en_ewt/index.html) and [GUM](https://universaldependencies.org/treebanks/en_gum/index.html).

**Encoder:** `microsoft/deberta-v3-xsmall` (frozen weights not included — loaded from HuggingFace at runtime)
**Custom head:** `biaffine_head.safetensors` — word projection, arc/rel/POS MLPs and biaffine layers
**Labels:** 53 DEPREL labels · 19 UPOS tags
**Score convention:** `s_arc[dep, head]`, `s_rel[dep, head, rel]`

## Metrics (EWT + GUM, decode: Eisner (projective MST))

| Split | LAS | UPOS | UCM | LCM |
|-------|-----|------|-----|-----|
| dev   | 93.03% | 98.09% | 70.75% | 60.96% |
| test  | 92.97% | 98.04% | 70.23% | 60.91% |


## ONNX / production use

`model.onnx` — fp32 model (Recommended for CPU inference).
`model.fp16.onnx` — fp16 model (For GPU or environments with native fp16 support, ~~139 MB).

Inputs: `subwords [B, W, 20]` int64. Outputs: `s_arc [B,W,W]`, `s_rel [B,W,W,R]`, `s_pos [B,W,P]`.

```bash
# download only inference artifacts
hf download ghotriw/deberta-v3-xsmall-biaffine-dep-pos-en-ewt-gum \
  model.fp16.onnx model.onnx vocabs.json tokenizer.json \
  --local-dir ./model
```

`vocabs.json` — DEPREL and UPOS vocabularies (str→int dicts).

## Input format

The model expects a **word-level subword grid** `[B, W, fix_len=20]` (int64),
where each word is independently tokenised with the encoder's sentencepiece tokeniser
and padded/truncated to 20 subword slots. Position 0 is a synthetic ROOT word
whose only subword is `[CLS]` (id 1).

## Vocabularies

`config.json` contains `rel_vocab` (str→int) and `pos_vocab` (str→int).
Index 0 is the `<pad>` / ROOT slot and should be ignored in evaluation.