Text Classification
Transformers
PyTorch
TensorBoard
mpnet
Generated from Trainer
text-embeddings-inference
Instructions to use mtyrrell/CPU_Conditional_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mtyrrell/CPU_Conditional_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mtyrrell/CPU_Conditional_Classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mtyrrell/CPU_Conditional_Classifier") model = AutoModelForSequenceClassification.from_pretrained("mtyrrell/CPU_Conditional_Classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from mtyrrell/CPU_Conditional_Classifier: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/mtyrrell/CPU_Conditional_Classifier/resolve/refs%2Fpr%2F2/model.safetensors
- Command line
-
hf download hf://mtyrrell/CPU_Conditional_Classifier@refs/pr/2/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/mtyrrell/CPU_Conditional_Classifier/resolve/refs%2Fpr%2F2/model.safetensors
438 MB
- Xet hash:
- 65b195c22725a56ed2ec2d07652543dba791da2ce998970626779e472f38f7a2
- Size of remote file:
- 438 MB
- SHA256:
- f1a119875c1b829076b1a555c003a368092b1bfec6c5cc535046847cf90f593f
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