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# Fusion NER Models
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| Basic | Basic training on IAHALT | [https://huggingface.co/FusioNER/Basic_IAHALT](https://huggingface.co/FusioNER/Basic_IAHALT) | IAHALT |
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| Vitaly | Vitaly training on IAHALT (with BI-BI problem) | [https://huggingface.co/FusioNER/Vitaly_NER](https://huggingface.co/FusioNER/Vitaly_NER) | IAHALT |
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| NEMO | Training on NEMO dataset| [https://huggingface.co/FusioNER/Nemo/tree/main](https://huggingface.co/FusioNER/Nemo) | NEMO |
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| IAHALT_and_NEMO | Basic training on IAHALT + NEMO | [https://huggingface.co/FusioNER/IAHALT_and_NEMO](https://huggingface.co/FusioNER/IAHALT_and_NEMO) | IAHALT + NEMO |
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| IAHALT_and_NEMO_PP | Training on IAHALT + NEMO + Name-Sentences[1] + Entity-Injection[2] | [https://huggingface.co/FusioNER/IAHALT_and_NEMO_and_PP](https://huggingface.co/FusioNER/IAHALT_and_NEMO_and_PP) | IAHALT + NEMO |
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[1] Name-Sentences: Adding to the corpus sentences that contain only the entity we want the network to learn.
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[2] Entity-Injection: Replace tagged entity in the original corpus with new entity. By using, this method, the model can learn new entities (not labels!) which the model not extracted before.
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# Fusion NER Models
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Here you can find our NER models:
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|model name | model description | model path | datasets |
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| Basic | Basic training on IAHALT | [https://huggingface.co/FusioNER/Basic_IAHALT](https://huggingface.co/FusioNER/Basic_IAHALT) | IAHALT |
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| Vitaly | Vitaly training on IAHALT (with BI-BI problem) | [https://huggingface.co/FusioNER/Vitaly_NER](https://huggingface.co/FusioNER/Vitaly_NER) | IAHALT |
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| NEMO | Training on NEMO dataset| [https://huggingface.co/FusioNER/Nemo/tree/main](https://huggingface.co/FusioNER/Nemo) | NEMO |
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| IAHALT_and_NEMO | Basic training on IAHALT + NEMO | [https://huggingface.co/FusioNER/IAHALT_and_NEMO](https://huggingface.co/FusioNER/IAHALT_and_NEMO) | IAHALT + NEMO |
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| IAHALT_and_NEMO_PP | Training on IAHALT + NEMO + Name-Sentences[1] + Entity-Injection[2] | [https://huggingface.co/FusioNER/IAHALT_and_NEMO_and_PP](https://huggingface.co/FusioNER/IAHALT_and_NEMO_and_PP) | IAHALT + NEMO |
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| Animals | Training on IAHALT + Entity-Injection[2] (of animals names as PER entities) | [https://huggingface.co/FusioNER/Animals](https://huggingface.co/FusioNER/Animals) | IAHALT |
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| PRS-Injection | Training on IAHALT + Entity-Injection[2] (of PRS names as PER entities) | [https://huggingface.co/FusioNER/PRS-Injection](https://huggingface.co/FusioNER/PRS-Injection) | IAHALT |
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[1] Name-Sentences: Adding to the corpus sentences that contain only the entity we want the network to learn.
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[2] Entity-Injection: Replace a tagged entity in the original corpus with a new entity. By using, this method, the model can learn new entities (not labels!) which the model not extracted before.
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