Text Classification
Transformers
PyTorch
TensorBoard
mpnet
Generated from Trainer
text-embeddings-inference
Instructions to use mtyrrell/CPU_Netzero_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mtyrrell/CPU_Netzero_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mtyrrell/CPU_Netzero_Classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mtyrrell/CPU_Netzero_Classifier") model = AutoModelForSequenceClassification.from_pretrained("mtyrrell/CPU_Netzero_Classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mtyrrell/CPU_Netzero_Classifier: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/mtyrrell/CPU_Netzero_Classifier/resolve/3c4be43f61748be4c01fa23e308d91e3d39eb941/pytorch_model.bin
- Command line
-
hf download hf://mtyrrell/CPU_Netzero_Classifier@3c4be43f61748be4c01fa23e308d91e3d39eb941/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mtyrrell/CPU_Netzero_Classifier/resolve/3c4be43f61748be4c01fa23e308d91e3d39eb941/pytorch_model.bin
438 MB
- Xet hash:
- 98312f60dd519896650fc79a6b7a7bb85af0fd28accc849fc8019178d85f319f
- Size of remote file:
- 438 MB
- SHA256:
- f6cac0aac44845e881191ed94a00157a22eac1a14eb9f1c01fbe1fc332348ff5
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