Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use DipanAI/test_bug_temporary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DipanAI/test_bug_temporary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DipanAI/test_bug_temporary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DipanAI/test_bug_temporary") model = AutoModelForSequenceClassification.from_pretrained("DipanAI/test_bug_temporary") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f77fd916dc7b4507dba462edc53223bdf4eb9388fbf1d06b1b4616565673e241
- Size of remote file:
- 433 MB
- SHA256:
- 9ed75041345e3e06cb38d7b04ce0791e8dedc8b6db48a52ddf1a2a12b1463d00
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