Text Classification
Transformers
TensorBoard
Safetensors
English
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use gokulsrinivasagan/bert_uncased_L-4_H-128_A-2_rte with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gokulsrinivasagan/bert_uncased_L-4_H-128_A-2_rte with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gokulsrinivasagan/bert_uncased_L-4_H-128_A-2_rte")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gokulsrinivasagan/bert_uncased_L-4_H-128_A-2_rte") model = AutoModelForSequenceClassification.from_pretrained("gokulsrinivasagan/bert_uncased_L-4_H-128_A-2_rte") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- deee9630cc8a05cd25f7809eb575221f8ef9f77300a45ad5bc12a8db1a91e992
- Size of remote file:
- 19.1 MB
- SHA256:
- 3c74d8f5ed13a1e31e1128a7bb7ade391cabae902429ea7ff83ccf1c35b696d5
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