Token Classification
Transformers
PyTorch
TensorBoard
Safetensors
English
distilbert
Generated from Trainer
Instructions to use vishnun/knowledge-graph-nlp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vishnun/knowledge-graph-nlp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="vishnun/knowledge-graph-nlp")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("vishnun/knowledge-graph-nlp") model = AutoModelForTokenClassification.from_pretrained("vishnun/knowledge-graph-nlp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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# knowledge-graph-nlp
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the
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It achieves the following results on the evaluation set:
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- Loss: 0.1830
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- Precision: 0.8988
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# knowledge-graph-nlp
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the [vishnun/NLP-KnowledgeGraph](https://huggingface.co/datasets/vishnun/NLP-KnowledgeGraph) dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1830
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- Precision: 0.8988
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