Instructions to use avinasht/FLANG-ELECTRA_bert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use avinasht/FLANG-ELECTRA_bert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="avinasht/FLANG-ELECTRA_bert-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("avinasht/FLANG-ELECTRA_bert-base-uncased") model = AutoModelForSequenceClassification.from_pretrained("avinasht/FLANG-ELECTRA_bert-base-uncased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 024f27323041010035c31c5e7fe1205c1f3a35e26aabd99d4579878e2182273a
- Size of remote file:
- 4.66 kB
- SHA256:
- ea2155b52228ca40ca1b54d932cc2a5d5ede44229b254bb6e5ffa6a9eab0a0e2
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