Instructions to use 0x7o/rubert-base-massive-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 0x7o/rubert-base-massive-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="0x7o/rubert-base-massive-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("0x7o/rubert-base-massive-ner") model = AutoModelForTokenClassification.from_pretrained("0x7o/rubert-base-massive-ner") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
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by librarian-bot - opened
README.md
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datasets:
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- massive
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model-index:
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- name: rubert-base-massive-ner
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results: []
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license: apache-2.0
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language:
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pipeline_tag: token-classification
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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language:
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- ru
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license: apache-2.0
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datasets:
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- massive
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pipeline_tag: token-classification
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base_model: DeepPavlov/rubert-base-cased
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model-index:
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- name: rubert-base-massive-ner
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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