Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use ArchitJamb/Encoded_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArchitJamb/Encoded_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ArchitJamb/Encoded_Model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ArchitJamb/Encoded_Model") model = AutoModelForSequenceClassification.from_pretrained("ArchitJamb/Encoded_Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5840663def3ec87cbeef5eefeca95eb66433a099cb73cd66994c41a6f469f827
- Size of remote file:
- 4.6 kB
- SHA256:
- 6ca1f2077a09de3a1c4c581d7b8108c5695a86ea127704d549ce340eca043972
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