Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use MelikeErdogan/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MelikeErdogan/output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MelikeErdogan/output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MelikeErdogan/output") model = AutoModelForSequenceClassification.from_pretrained("MelikeErdogan/output") - Notebooks
- Google Colab
- Kaggle
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README.md
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## Model description
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## Intended uses & limitations
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## Model description
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This model gives the probabality values that calculate the result of LABEL 1 if the given sentences are positive, and LABEL 0 if they are negative, together with their values.
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## Intended uses & limitations
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