| from transformers import pipeline | |
| # ──────────────────────────────────────────────────────────────── | |
| # 2. Token Classification / NER | |
| # ──────────────────────────────────────────────────────────────── | |
| # Default model: dbmdz/bert-large-cased-finetuned-conll03-english | |
| # → Used for: standard English NER (PER, ORG, LOC, MISC) | |
| # trained on CoNLL-2003 → reliable on news/articles | |
| # but weaker on social media / Indian names/cities | |
| # | |
| # Alternative model: dslim/bert-base-NER | |
| # → Used for: lighter & faster version (110M vs 340M params) | |
| # still strong on standard entities, popular choice | |
| #pipe = pipeline("ner", aggregation_strategy="simple") | |
| pipe = pipeline("ner", model="dslim/bert-base-NER", aggregation_strategy="simple") | |
| print(pipe("kapil is from pathankot")) |