Instructions to use Maaly/host with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Maaly/host with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Maaly/host")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Maaly/host") model = AutoModelForTokenClassification.from_pretrained("Maaly/host") - Notebooks
- Google Colab
- Kaggle
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host model is a Named Entity Recognition (NER) model that identifies and annotates the host (living organism) of microbiome samples in texts.
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Testing examples:
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1. Turkestan cockroach nymphs (Finke, 2013) were fed to the treefrogs at a quantity of 10% of treefrog biomass twice a week.
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host model is a Named Entity Recognition (NER) model that identifies and annotates the host (living organism) of microbiome samples in texts.
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The model is a fine-tuned BioBERT model and the training dataset is available in https://gitlab.com/maaly7/emerald_metagenomics_annotations
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Testing examples:
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1. Turkestan cockroach nymphs (Finke, 2013) were fed to the treefrogs at a quantity of 10% of treefrog biomass twice a week.
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