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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- be605b2b0abfe79ffb91fbd845cb7bdec002426f83ca2afbe43c7564d9396e76
- Size of remote file:
- 433 MB
- SHA256:
- a913dda980922bb07dfbeb9736e1a1a299ec39fd6e4f101a539e8cc29621cae4
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