Token Classification
Transformers
Safetensors
English
roberta
feature-extraction
entity-recognition
foundation-model
RoBERTa
generic
Instructions to use numind/NuNER-v2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use numind/NuNER-v2.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="numind/NuNER-v2.0")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("numind/NuNER-v2.0") model = AutoModel.from_pretrained("numind/NuNER-v2.0") - Notebooks
- Google Colab
- Kaggle
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# SOTA Entity Recognition English Foundation Model by NuMind 🔥
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This model provides
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**Checkout other models by NuMind:**
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* SOTA Multilingual Entity Recognition Foundation Model: [link](https://huggingface.co/numind/entity-recognition-multilingual-general-sota-v1)
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* SOTA Sentiment Analysis Foundation Model: [English](https://huggingface.co/numind/generic-sentiment-v1), [Multilingual](https://huggingface.co/numind/generic-sentiment-multi-v1)
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# SOTA Entity Recognition English Foundation Model by NuMind 🔥
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This model provides embeddings for the Entity Recognition task in English. It is an improved version of the model from our [**paper**](https://arxiv.org/abs/2402.15343).
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**Checkout other models by NuMind:**
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* SOTA Zero-shot NER Model [NuNER Zero](https://huggingface.co/numind/NuNER_Zero)
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* SOTA Multilingual Entity Recognition Foundation Model: [link](https://huggingface.co/numind/entity-recognition-multilingual-general-sota-v1)
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* SOTA Sentiment Analysis Foundation Model: [English](https://huggingface.co/numind/generic-sentiment-v1), [Multilingual](https://huggingface.co/numind/generic-sentiment-multi-v1)
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