Text Classification
Transformers
PyTorch
TensorBoard
mpnet
Generated from Trainer
text-embeddings-inference
Instructions to use ppsingh/mpnet-adaptation_mitigation-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ppsingh/mpnet-adaptation_mitigation-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ppsingh/mpnet-adaptation_mitigation-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ppsingh/mpnet-adaptation_mitigation-classifier") model = AutoModelForSequenceClassification.from_pretrained("ppsingh/mpnet-adaptation_mitigation-classifier") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:a29d59b67315aa19e1306cb31634749aafe94afa375ab8bf9e61867994ae621c
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size 437979400
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