Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use cdc-hf/bert-platform-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cdc-hf/bert-platform-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cdc-hf/bert-platform-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cdc-hf/bert-platform-classifier") model = AutoModelForSequenceClassification.from_pretrained("cdc-hf/bert-platform-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a096ef0470ea35ef32b3a3bc7c32a4148dcd2b9d282a56fa532164a844f49124
- Size of remote file:
- 438 MB
- SHA256:
- 9d8b322127748ad2787ac88c001f4957e2e52f6704dcfd415516ea7eb33e490c
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