Text Classification
Transformers
PyTorch
Turkish
bert
deprem-clf-v1
Eval Results (legacy)
text-embeddings-inference
Instructions to use deprem-ml/deprem_bert_128k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deprem-ml/deprem_bert_128k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="deprem-ml/deprem_bert_128k")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("deprem-ml/deprem_bert_128k") model = AutoModelForSequenceClassification.from_pretrained("deprem-ml/deprem_bert_128k") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 28ad872f3162c51f5401fd0d67a2e60537fcbe89257a83fef691d13e5975fe4e
- Size of remote file:
- 737 MB
- SHA256:
- 85612c6a9e63ad6ac9493561cc857f0e3509dd41d474ebeb85cc354f39962f0f
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