Text Classification
Transformers
Safetensors
English
bert
Generated from Trainer
text-embeddings-inference
Instructions to use ADS509/experiment_labels_bert_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ADS509/experiment_labels_bert_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ADS509/experiment_labels_bert_base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ADS509/experiment_labels_bert_base") model = AutoModelForSequenceClassification.from_pretrained("ADS509/experiment_labels_bert_base") - Notebooks
- Google Colab
- Kaggle
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The full code used for training is below
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tokenizer = AutoTokenizer.from_pretrained("bert-base_uncased")
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# Function to tokenize data with
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The full code used for training is below
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```python
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tokenizer = AutoTokenizer.from_pretrained("bert-base_uncased")
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# Function to tokenize data with
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