Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Cagatayd/emotion-classif-testt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cagatayd/emotion-classif-testt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cagatayd/emotion-classif-testt")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cagatayd/emotion-classif-testt") model = AutoModelForSequenceClassification.from_pretrained("Cagatayd/emotion-classif-testt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 32f7d702b5b6c6136a6d99c25494d0340c04296c20debfa073cc0b03ff777029
- Size of remote file:
- 5.11 kB
- SHA256:
- 0545c8aeef96e3f5a0401ce6873a6a7bb9f80774778679c07f6f304c8c26bfb2
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