Text Classification
Transformers
PyTorch
TensorBoard
mpnet
Generated from Trainer
text-embeddings-inference
Instructions to use mtyrrell/CPU_Mitigation_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mtyrrell/CPU_Mitigation_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mtyrrell/CPU_Mitigation_Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mtyrrell/CPU_Mitigation_Classifier") model = AutoModelForSequenceClassification.from_pretrained("mtyrrell/CPU_Mitigation_Classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download modules.json from mtyrrell/CPU_Mitigation_Classifier: direct link, hf CLI and curl.
- Browser
- Download file 349 Bytes
-
https://huggingface.co/mtyrrell/CPU_Mitigation_Classifier/resolve/refs%2Fpr%2F1/modules.json
- Command line
-
hf download hf://mtyrrell/CPU_Mitigation_Classifier@refs/pr/1/modules.json
-
curl -L -o modules.json https://huggingface.co/mtyrrell/CPU_Mitigation_Classifier/resolve/refs%2Fpr%2F1/modules.json
349 Bytes
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": "", | |
| "type": "sentence_transformers.models.Transformer" | |
| }, | |
| { | |
| "idx": 1, | |
| "name": "1", | |
| "path": "1_Pooling", | |
| "type": "sentence_transformers.models.Pooling" | |
| }, | |
| { | |
| "idx": 2, | |
| "name": "2", | |
| "path": "2_Normalize", | |
| "type": "sentence_transformers.models.Normalize" | |
| } | |
| ] |