Text Classification
Transformers
Safetensors
Turkish
bert
turkish
nlp
turn-detection
voice-assistant
latency-optimization
siriusai
production-ready
enterprise
Eval Results (legacy)
text-embeddings-inference
Instructions to use hayatiali/turn-detector-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hayatiali/turn-detector-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hayatiali/turn-detector-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hayatiali/turn-detector-v2") model = AutoModelForSequenceClassification.from_pretrained("hayatiali/turn-detector-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac206edc650eb6237fe5ff2d856b8bda375475abce967337df45360ec0ee7782
- Size of remote file:
- 5.84 kB
- SHA256:
- 6ce37056b653bec41c689d47ad2e5467eee5c03e8e20cf17c2a79dd05dfaa8f1
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