Instructions to use akadhim-ai/bert_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akadhim-ai/bert_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="akadhim-ai/bert_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("akadhim-ai/bert_model") model = AutoModelForSequenceClassification.from_pretrained("akadhim-ai/bert_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d202b6b81d2d7f78c508175812421c4400880caf517d7304d34f3b921a23491
- Size of remote file:
- 268 MB
- SHA256:
- e3eb92603fd221163261ad7f6702e397b182651850251d6255b44a729585c0f9
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