Kernels
kernel
governance
provenance
suite
embedding-table
not-a-transformers-config
doi:10.5281/zenodo.19944926
Instructions to use SZLHOLDINGS/szl-kernels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Kernels
How to use SZLHOLDINGS/szl-kernels with Kernels:
# !pip install kernels from kernels import get_kernel # a version (or an explicit revision) is required; see the "Files and versions" tab for the available ones kernel = get_kernel("SZLHOLDINGS/szl-kernels", version=1) - Notebooks
- Google Colab
- Kaggle
Forge SZL-MiniEmbed v1: REAL trained embeddings (co-occurrence+PPMI+TruncatedSVD, no gensim) + vocab/config + receipt + eval + bundled corpus + honest card & provenance
7842caa verified Download config.json from SZLHOLDINGS/szl-kernels: direct link, hf CLI and curl.
- Browser
- Download file 399 Bytes
-
https://huggingface.co/SZLHOLDINGS/szl-kernels/resolve/main/config.json
- Command line
-
hf download hf://SZLHOLDINGS/szl-kernels/config.json
-
curl -L -o config.json https://huggingface.co/SZLHOLDINGS/szl-kernels/resolve/main/config.json
399 Bytes
| { | |
| "model": "SZL-MiniEmbed", | |
| "method": "term-term co-occurrence (distance-weighted, window=5) -> PPMI -> TruncatedSVD", | |
| "dim": 128, | |
| "vocab_size": 3290, | |
| "min_count": 5, | |
| "window": 5, | |
| "seed": 20260721, | |
| "normalization": "L2 row-normalized", | |
| "files": { | |
| "vectors": "vectors.npz (key 'vectors', float32 [V,dim])", | |
| "vocab": "vocab.json ({'vocab':[term...], 'index':{term:i}})" | |
| } | |
| } |