Text Classification
Transformers
Safetensors
English
bert
PyTorch
multi-class-classification
text-embeddings-inference
Instructions to use AIPsy/bert-base-client-topic-classification-eng with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AIPsy/bert-base-client-topic-classification-eng with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AIPsy/bert-base-client-topic-classification-eng")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AIPsy/bert-base-client-topic-classification-eng") model = AutoModelForSequenceClassification.from_pretrained("AIPsy/bert-base-client-topic-classification-eng") - Notebooks
- Google Colab
- Kaggle
Upload BertForSequenceClassification
Browse files- config.json +1 -3
- model.safetensors +2 -2
config.json
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"initializer_range": 0.02,
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model.safetensors
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size 438097044
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