Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use eskayML/interview_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eskayML/interview_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eskayML/interview_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("eskayML/interview_classifier") model = AutoModelForSequenceClassification.from_pretrained("eskayML/interview_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 50d39d640916968fd38b6bcc0323deab192e7f5198de2503621edd263a068155
- Size of remote file:
- 268 MB
- SHA256:
- c746289e38cf0dc9354955351115fe44941e54e64e6a5c7bd35c7bd70ab81c5f
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