Text Classification
Transformers
PyTorch
Turkish
bert
deprem-clf-v1
Eval Results (legacy)
text-embeddings-inference
Instructions to use deprem-ml/multilabel_earthquake_tweet_intent_bert_base_turkish_cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deprem-ml/multilabel_earthquake_tweet_intent_bert_base_turkish_cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="deprem-ml/multilabel_earthquake_tweet_intent_bert_base_turkish_cased")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("deprem-ml/multilabel_earthquake_tweet_intent_bert_base_turkish_cased") model = AutoModelForSequenceClassification.from_pretrained("deprem-ml/multilabel_earthquake_tweet_intent_bert_base_turkish_cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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