Text Classification
Transformers
TensorBoard
Safetensors
albert
Generated from Trainer
Eval Results (legacy)
Instructions to use indukurs/albert_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use indukurs/albert_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="indukurs/albert_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("indukurs/albert_model") model = AutoModelForSequenceClassification.from_pretrained("indukurs/albert_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7d2b19c813a5761f921e5b7ae25c4ee5c832c245e72228e802de1520ddceb63
- Size of remote file:
- 4.66 kB
- SHA256:
- 7521b5e8c10d49d76c034d8bfef34bfff6d33a93fbbddf97ced1afea69b1d0c0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.