Text Classification
Transformers
PyTorch
Safetensors
English
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use whispAI/bert-claimcoherence-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use whispAI/bert-claimcoherence-mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="whispAI/bert-claimcoherence-mini")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("whispAI/bert-claimcoherence-mini") model = AutoModelForSequenceClassification.from_pretrained("whispAI/bert-claimcoherence-mini", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (f5d7827ae627e34a9ee51fed65d62ab2425d1920) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>101d5f5
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Commit From AutoTrain
6ae3006 -
initial commit
25dbe2a