Token Classification
Transformers
Safetensors
Norwegian
Norwegian Bokmål
Generated from Trainer
custom_code
Instructions to use Kushtrim/norbert3-large-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kushtrim/norbert3-large-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Kushtrim/norbert3-large-ner", trust_remote_code=True)# Load model directly from transformers import AutoModelForTokenClassification model = AutoModelForTokenClassification.from_pretrained("Kushtrim/norbert3-large-ner", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
CVE-2026-1839
#1
by Marentius - opened
What this fixes
transformers 5+ expects PreTrainedModel.post_init() to run so internal fields like all_tied_weights_keys exist. This repo’s remote modeling_norbert.py never called post_init(), which caused: AttributeError: 'NorbertForTokenClassification' object has no attribute 'all_tied_weights_keys' when loading with trust_remote_code=True (e.g. Docker builds).
What changed
- self.post_init() after the base NorbertModel modules are built.
- self.post_init() after task heads (Classifier) are added, and for NorbertForMaskedLM, matching the pattern used in ltg/norbert3-large.
Notes
- No weight or config.json changes — Python-only.
- Relates to CVE-2026-1839 in the sense that projects need transformers 5+; this unblocks loading with current transformers.
Marentius changed pull request status to open
Kushtrim changed pull request status to merged