Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use CbI3PAHb/my_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CbI3PAHb/my_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CbI3PAHb/my_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CbI3PAHb/my_model") model = AutoModelForSequenceClassification.from_pretrained("CbI3PAHb/my_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a741efcc94b72d98697ec3363d5cc08e846f990f8e50767b6e2d5c8b2a9a8678
- Size of remote file:
- 711 MB
- SHA256:
- 4b1a1bd216eaf325b6f2f85b4ec895385f2ece497ebac098a7e55e5359eea004
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