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
|
Download README.md from kloodia/laya-executorch: direct link, hf CLI and curl.
- Browser
- Download file 914 Bytes
-
https://huggingface.co/kloodia/laya-executorch/resolve/main/README.md
- Command line
-
hf download hf://kloodia/laya-executorch/README.md
-
curl -L -o README.md https://huggingface.co/kloodia/laya-executorch/resolve/main/README.md
914 Bytes
| license: apache-2.0 | |
| language: | |
| - multilingual | |
| tags: | |
| - executorch | |
| - decision-model | |
| - laya | |
| - localia | |
| base_model: convaiinnovations/laya | |
| # Laya multilingual ExecuTorch (Localia gate) | |
| Exported from [`convaiinnovations/laya`](https://huggingface.co/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` | — | 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 ≈ -1e4) | |
| ## License | |
| Apache-2.0 (same as upstream Convai Innovations Laya). | |