Instructions to use pooria/foxmind with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use pooria/foxmind with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('token-classification', 'pooria/foxmind'); - GLiNER2
How to use pooria/foxmind with GLiNER2:
from gliner2 import AutoExtractor extractor = AutoExtractor.from_pretrained("pooria/foxmind") # Extract entities text = "Apple CEO Tim Cook announced iPhone 15 in Cupertino yesterday." result = extractor.extract_entities(text, ["company", "person", "product", "location"]) print(result) - Notebooks
- Google Colab
- Kaggle
foxmind
foxmind is the on-device decision model of foxpilot, a browser agent for Firefox. It is an ONNX export of the agent graph of GLiNER2 multi-v1, with a batch axis.
Base model: fastino/gliner2-multi-v1 (Apache-2.0), by Fastino.
It is the same single-graph export as onnx-community/gliner2-multi-v1-agent-ONNX, with one change: every input and output has a batch axis.
| Name | Shape |
|---|---|
input_ids, attention_mask |
[batch, seq] |
word_positions |
[batch, words] |
schema_positions |
[batch, schema] |
cls_logits |
[batch, schema - 1] |
count_logits |
[batch, 20] |
span_logits |
[batch, schema - 1, words, 8] |
At batch 1 it behaves like the original export. Pad shorter rows with 0 and set their mask to 0.
Files
onnx/model.onnx+model.onnx_data: fp32onnx/model_fp16.onnx+model_fp16.onnx_data: fp16
Accuracy
export/verify_onnx.py in the foxpilot repository checks this export. In fp32, 14 reference calls match the Python library, and each padded batch row matches its single call within 8.0e-6 on label and span scores.
Speed
Firefox 157, WebGPU, fp32: one call with 4 prompts takes 517 ms, against 1,242 ms for 4 single calls (2.4x).
License
Apache-2.0, the license of the base model. Export scripts: pooriaarab/foxpilot (MIT).
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Model tree for pooria/foxmind
Base model
fastino/gliner2-multi-v1