---
library_name: onnx
license: apache-2.0
pipeline_tag: token-classification
base_model: fastino/gliner2.5-multi-v1
tags:
- onnx
- gliner2
- gliner2.5
- boundary
- webgpu
- token-classification
- text-classification
- relation-extraction
---

# gliner2.5-multi-v1-onnx

ONNX export of [fastino/gliner2.5-multi-v1](https://huggingface.co/fastino/gliner2.5-multi-v1) (GLiNER 2.5
`BoundaryExtractor`) for onnxruntime-web / WebGPU. Revision 5 graphs plus
`attrs.onnx` (`score_explicit_spans`).

One encoder pass. JointIE beam, classification `implies`/`excludes`, record
assignment, and long-document chunking stay in JavaScript.

Host: [Pastel-Org/gliner2.5-onnx-webgpu](https://github.com/Pastel-Org/gliner2.5-onnx-webgpu)
(live: [gliner25-onnx-webgpu.pages.dev](https://gliner25-onnx-webgpu.pages.dev)).

## Files

| File | Role | Size |
|------|------|------|
| `onnx/model.onnx` | Encoder + entity pair path + classifier + `text_states` + `candidate_states` | 1121.5 MB |
| `onnx/heads.onnx` | `SparseRelationScorer` only (no encoder) | 23.7 MB |
| `onnx/records.onnx` | RecordHead assignment (inst/field/cand projections + null column) | 1.19 MB |
| `onnx/attrs.onnx` | `score_explicit_spans` (dynamo; pad 512/8/16) | 7.38 MB |

## attrs.onnx

Dynamo export of `head.score_explicit_spans`. Traced at 512 words, 8 attribute
queries, 16 spans. The JS host crops a 512-word window around the mention; that
pad is not a document-length cap. ORT vs torch RMSE ~1e-6 (small) / ~2e-6
(base, multi). Overlay lookup is the fallback if this graph fails to load.

## Decode notes (JS host, not this graph)

Attribute labels are packed with entity labels in one `[E]` block (sorted).
Single-label attributes use softmax. ONNX `pair_valid` is all-true; the host
drops `start >= end` slots before overlap.

Python `max_len` is 4096 words: `classify_text` / `extract` is **one
forward pass** over the whole document. That is what Fastino means by
long-context classification on CUDA/CPU.

This WebGPU export is not that:

| Call | Words in one GPU run | Measured here (M2 Max, onnxruntime-web) |
|------|----------------------|------------------------------------------|
| `classify_text` / `extract` | the whole string (cap 4096) | **small** finished 4096 words. **base** and **multi** died between 3500 and 3600 (`createCommandEncoder` / `std::bad_alloc`). |
| `classify_text_long` / `extract_entities_long` | **384**, overlap **64** | 4096-word docs: 13 windows. base 2.75 s, multi 4.3 s. Merge is max-confidence (classify) or span overlap (NER). |

A 4096-word `classify_text_long` never builds a 4096-word attention matrix.
Use the `*_long` APIs for contracts on base/multi in the browser.

## Still not in ONNX

Full Kleene classification AST is not ported; README `implies` / `excludes`
is a JS beam. Latent / anchorless records are not exported.

## Credits

- Base checkpoints: [Fastino](https://fastino.ai), Apache-2.0.
- ONNX export + JS host: [Pastel-Cloud OÜ](https://github.com/Pastel-Org).