Text Classification
Transformers
PyTorch
bert
classification
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use EstherT/sentence-acceptability with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EstherT/sentence-acceptability with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="EstherT/sentence-acceptability")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("EstherT/sentence-acceptability") model = AutoModelForSequenceClassification.from_pretrained("EstherT/sentence-acceptability") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:f8430902527b127edd25adf5db35a7afecb6dbffc9b4bcf2ec6a24662b239d80
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size 437962832
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