Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use poooj/bert_test_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use poooj/bert_test_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="poooj/bert_test_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("poooj/bert_test_model") model = AutoModelForSequenceClassification.from_pretrained("poooj/bert_test_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2584a61d5980624ce5d4cbade1b7b7d3646d6d905195cae7c17f3c7b2b815d6c
- Size of remote file:
- 438 MB
- SHA256:
- b4d90e566a58926cdd73867f6f002ce0e1343312576cde30e55f1fc278232f80
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