Instructions to use amjad101/bert-base-v2-args with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amjad101/bert-base-v2-args with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="amjad101/bert-base-v2-args")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("amjad101/bert-base-v2-args") model = AutoModelForSequenceClassification.from_pretrained("amjad101/bert-base-v2-args") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 95e1ab35ea23d9b1165e549e9830078cb837e1d509b09d146e8ab7e7d223393f
- Size of remote file:
- 3.52 kB
- SHA256:
- 4853a976573887a0f92ac64e494be42db614f85ba848c22ad5a8ccc87f87b3c5
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