MODEL INTELLIGENCE · SOURCE-FIRST
What is wikineural-multilingual-ner?
Open Model Weights records wikineural-multilingual-ner as a 0.17727B-parameter text open-weight model in the wikineural-multilingual-ner family, with Babelscape listed as the developer. The checked source repository provides 3 recognized weight artifacts, format evidence for Safetensors, PyTorch and a verified context window of 512 tokens. Values that are not evidenced in the checked sources remain explicitly undisclosed or unknown.
The repository declares ['cc-by-nc-sa-4.0']. Commercial-use status requires manual review. Open Model Weights reports the checked license evidence and classification; this is not legal advice.
No base model is declared in the checked standard lineage metadata, so Open Model Weights does not infer one. In the checked repository, training or recipe evidence is present and a data-disclosure signal is present.
DEPLOYMENT PROFILE
Weight memory, without pretending it is a deployment guarantee.
These bars visualize weight-only decimal-GB estimates. They exclude KV cache, activations, runtime overhead, optimizer state and sharding.
LICENSE & USE
['cc-by-nc-sa-4.0']
Commercial-use status requires manual review
This section summarizes the checked repository evidence. It is not legal advice.
LINEAGE & PROVENANCE
What the checked sources disclose — and what they do not.
Open Model Weights does not infer a hidden base model or training corpus when the checked sources do not declare one.
RUNTIME SIGNALS
Compatibility claims stay attached to their evidence level.
Declared and model-card-mentioned runtimes are discovery signals. They are not treated as Open Model Weights runtime tests unless explicitly measured.
EVIDENCE TRAIL
Sources and observed history.
This is where the article remains auditable: source links on one side, the registry's observed change history on the other.
Checked Hugging Face API metadata, exact repository file list, model card and config when accessible.
Previous verification level: discovered-pending.