Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use KalaiselvanD/albert_model_03 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KalaiselvanD/albert_model_03 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KalaiselvanD/albert_model_03")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KalaiselvanD/albert_model_03") model = AutoModelForSequenceClassification.from_pretrained("KalaiselvanD/albert_model_03", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0cd434f8744fe475013012cbcf06f7225f056ff99498d9dc8f1621f04e37f965
- Size of remote file:
- 268 MB
- SHA256:
- 99e558fbe9d5c1611854a832d4ae821890af281d8436bf04e52946cbe6a90456
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