Text Classification
Scikit-learn
Joblib
English
nemotron
ollama
recipe-only
surrogate
recipe-conformance
sovereign-ai
governed-ai
szl-holdings
Instructions to use SZLHOLDINGS/szl-nemo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use SZLHOLDINGS/szl-nemo with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("SZLHOLDINGS/szl-nemo", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
fix: classify szl-nemo as an Ollama recipe, not NeMo weights
#1
by betterwithage - opened
Renames the standard Ollama Modelfile to stop false NeMo library inference, adds a registry/layer digest manifest, and clarifies the recipe/upstream-license boundary. No weights or measured benchmarks are added.
Validated before merge: card parses; PR tree contains only README, standard Modelfile, provenance manifest, and gitattributes; no weights; Hub library_name is no longer NeMo; Modelfile has one FROM/PARAMETER/SYSTEM; the live Ollama manifest, config, and layers match the pinned provenance file; upstream model/license links return HTTP 200.
betterwithage changed pull request status to merged