Instructions to use kloodia/laya-executorch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Laya
How to use kloodia/laya-executorch with Laya:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Laya multilingual ExecuTorch (Localia gate)
Exported from convaiinnovations/laya (subfolder=multilingual, mmBERT).
| Path | Backend | Quant | Size (approx) |
|---|---|---|---|
ios/laya_gate_mlx_int4.pte |
MLX | INT4 linear + INT8 embedding | ~280 MB |
android/laya_gate_xnnpack_8da4w.pte |
XNNPACK | 8DA4W linears (embeddings fp32) | ~830 MB |
*/tokenizer.json |
โ | mmBERT multilingual tokenizer | ~33 MB |
I/O
- Inputs:
input_ids[1,2048],attention_mask[1,2048],marker_pos[1,4],marker_mask[1,4],qtype[1](0=choice,1=score,2=noul) - Output:
logits[1,4](unused options masked โ -1e4)
License
Apache-2.0 (same as upstream Convai Innovations Laya).
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Base model
convaiinnovations/laya