Instructions to use GautamR/akai_ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GautamR/akai_ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="GautamR/akai_ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("GautamR/akai_ner") model = AutoModelForTokenClassification.from_pretrained("GautamR/akai_ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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license: apache-2.0
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language:
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- en
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library_name: transformers
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pipeline_tag: token-classification
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tags:
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- agriculture
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## Uses
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Helps extracting the crop name, pest names and seed details from a query asked.
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license: apache-2.0
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language:
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- en
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library_name: adapter-transformers
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pipeline_tag: token-classification
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tags:
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- agriculture
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## Uses
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Helps extracting the crop name, pest names and seed details from a query asked.
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