README.md

---
title: README
emoji: 📈
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colorTo: indigo
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<img src="https://raw.githubusercontent.com/asahi417/tner/master/asset/tner_logo_horizontal.png" alt="" width="150" style="margin-left:'auto' margin-right:'auto' display:'block'"/>

<br>

Hosting models and datasets for <a href="https://github.com/asahi417/tner">T-NER</a>, which is a python tool for language model fine-tuning on named-entity-recognition (NER) implemented in pytorch, available via [pip](https://pypi.org/project/tner/).

Install tner via pip,
<pre class="line-numbers">
   <code class="language-python">
      pip install tner
   </code>
</pre>
and play with NER models.
<pre class="line-numbers">
   <code class="language-python">
      from tner import TransformersNER
      model = TransformersNER('tner/roberta-large-conll2003')
      output = model.prediction(["Jacob Collier is a Grammy awarded artist from London"])
   </code>
</pre>

See more information bellow.
<ul>
   <li>&nbsp; - GitHub: <a href="https://github.com/asahi417/tner">https://github.com/asahi417/tner</a></li>
   <li>&nbsp; - Model List: <a href="https://github.com/asahi417/tner/blob/master/MODEL_CARD.md">https://github.com/asahi417/tner/blob/master/MODEL_CARD.md</a></li>
   <li>&nbsp; - Dataset List: <a href="https://github.com/asahi417/tner/blob/master/DATASET_CARD.md">https://github.com/asahi417/tner/blob/master/DATASET_CARD.md</a></li>
   <li>&nbsp; - Paper: <a href="https://aclanthology.org/2021.eacl-demos.7/">T-NER (EACL 2021 demo)</a>, <a href="https://arxiv.org/abs/2210.03797">TweetNER7 (AACL 2022 long paper)</a></li>
</ul>