Text Classification
Transformers
Safetensors
Turkish
bert
turkish
nlp
siriusai
production-ready
enterprise
Eval Results (legacy)
text-embeddings-inference
Instructions to use hayatiali/emotion-tr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hayatiali/emotion-tr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hayatiali/emotion-tr")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hayatiali/emotion-tr") model = AutoModelForSequenceClassification.from_pretrained("hayatiali/emotion-tr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 070082b830bf85bf8791bafd69a34500b5ac358ba48e0ce067a85b5779ff2cc9
- Size of remote file:
- 5.84 kB
- SHA256:
- 47d2c62ab98854e076dfcbd77ea4c345ec3702e73038f42b06c8586909d7b368
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