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:
- 1f2145e7b2cf0ee8ca59cf3a1e00b0541b8d8b33c5d21a1781203dd2076464eb
- Size of remote file:
- 3.45 kB
- SHA256:
- 072c66bdd2b3a4af78c99116fc9a3881568e3f5b680ecfc2dc63d84ef0d313d0
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