Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use KalaiselvanD/albert_model_02 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KalaiselvanD/albert_model_02 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KalaiselvanD/albert_model_02")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KalaiselvanD/albert_model_02") model = AutoModelForSequenceClassification.from_pretrained("KalaiselvanD/albert_model_02") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 593af65cdca3c1cc888057dd9b5028cbdf8a51001038d753cd862ec29cbc3ffe
- Size of remote file:
- 268 MB
- SHA256:
- 5abfd5e1d65482b0abcbf31ebaedd1df29be439e76d6e44aec45abf742e17ea2
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