Update README.md

README.md

@@ -4,4 +4,73 @@ datasets:
 language:
 - pl
 pipeline_tag: token-classification
----
+license: mit
+---
+# herbert-base-ner
+
+## Model description
+
+**herbert-base-ner** is a fine-tuned HerBERT model that can be used for **Named Entity Recognition** .
+It has been trained to recognize three types of entities: person (PER), location (LOC) and organization (ORG).
+
+Specifically, this model is an *allegro/herbert-base-cased* model that was fine-tuned on the Polish subset of *wikiann* dataset.
+
+
+## Intended uses & limitations
+
+#### How to use
+
+You can use this model with Transformers *pipeline* for NER.
+
+```python
+from transformers import AutoTokenizer, AutoModelForTokenClassification
+from transformers import pipeline
+
+tokenizer = AutoTokenizer.from_pretrained("pietruszkowiec/herbert-base-ner")
+model = AutoModelForTokenClassification.from_pretrained("pietruszkowiec/herbert-base-ner")
+
+nlp = pipeline("ner", model=model, tokenizer=tokenizer)
+example = "Nazywam się Grzegorz Brzęszczyszczykiewicz, pochodzę z Chrząszczyżewoszczyc"
+
+ner_results = nlp(example)
+print(ner_results)
+```
+
+### BibTeX entry and citation info
+
+```
+@inproceedings{mroczkowski-etal-2021-herbert,
+    title = "{H}er{BERT}: Efficiently Pretrained Transformer-based Language Model for {P}olish",
+    author = "Mroczkowski, Robert  and
+      Rybak, Piotr  and
+      Wr{\\'o}blewska, Alina  and
+      Gawlik, Ireneusz",
+    booktitle = "Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing",
+    month = apr,
+    year = "2021",
+    address = "Kiyv, Ukraine",
+    publisher = "Association for Computational Linguistics",
+    url = "https://www.aclweb.org/anthology/2021.bsnlp-1.1",
+    pages = "1--10",
+}
+```
+```
+@inproceedings{pan-etal-2017-cross,
+    title = "Cross-lingual Name Tagging and Linking for 282 Languages",
+    author = "Pan, Xiaoman  and
+      Zhang, Boliang  and
+      May, Jonathan  and
+      Nothman, Joel  and
+      Knight, Kevin  and
+      Ji, Heng",
+    booktitle = "Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
+    month = jul,
+    year = "2017",
+    address = "Vancouver, Canada",
+    publisher = "Association for Computational Linguistics",
+    url = "https://www.aclweb.org/anthology/P17-1178",
+    doi = "10.18653/v1/P17-1178",
+    pages = "1946--1958",
+    abstract = "The ambitious goal of this work is to develop a cross-lingual name tagging and linking framework for 282 languages that exist in Wikipedia. Given a document in any of these languages, our framework is able to identify name mentions, assign a coarse-grained or fine-grained type to each mention, and link it to an English Knowledge Base (KB) if it is linkable. We achieve this goal by performing a series of new KB mining methods: generating {``}silver-standard{''} annotations by transferring annotations from English to other languages through cross-lingual links and KB properties, refining annotations through self-training and topic selection, deriving language-specific morphology features from anchor links, and mining word translation pairs from cross-lingual links. Both name tagging and linking results for 282 languages are promising on Wikipedia data and on-Wikipedia data.",
+}
+```