Text Classification
Transformers
PyTorch
Safetensors
English
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use EricPeter/comments-text-classification-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EricPeter/comments-text-classification-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="EricPeter/comments-text-classification-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("EricPeter/comments-text-classification-model") model = AutoModelForSequenceClassification.from_pretrained("EricPeter/comments-text-classification-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c0428c05523b87ff8a97cba12a439ab5540bf8cbc330ef47808e749870e1a65
- Size of remote file:
- 1.33 GB
- SHA256:
- d8a44e8897e04b7868c8eab0d31de5b89859ac35f7fd87c9536489006a07eb77
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