Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use stepanom/stepanom_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stepanom/stepanom_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="stepanom/stepanom_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("stepanom/stepanom_model") model = AutoModelForSequenceClassification.from_pretrained("stepanom/stepanom_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4039bb67c43731d09a7101bcc29b43b284c9a4935106611f3db3701391b9a212
- Size of remote file:
- 4.92 kB
- SHA256:
- c021be67e8582016ab5a0e78b368346bf54553656bc3b335a224ae3245d06735
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