Text Classification
Transformers
PyTorch
Safetensors
English
bert
sentence-similarity
text-embeddings-inference
Instructions to use dennlinger/bert-wiki-paragraphs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dennlinger/bert-wiki-paragraphs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dennlinger/bert-wiki-paragraphs")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dennlinger/bert-wiki-paragraphs") model = AutoModelForSequenceClassification.from_pretrained("dennlinger/bert-wiki-paragraphs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 18f9223da9995069219dbbb2f7e3a763550dac0712670679668fe851551f7def
- Size of remote file:
- 438 MB
- SHA256:
- 6d80454cbc388be64d08cb4268f5b7cd00e4ad74c94f9e4fafa2d5b90da77b1d
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