Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use smerchi/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use smerchi/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="smerchi/test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("smerchi/test") model = AutoModelForSequenceClassification.from_pretrained("smerchi/test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ebf95a7e3b0b13000ec1c0099fa6cf07f44c5f1ed8ca0032e607f1d7272634b5
- Size of remote file:
- 5.11 kB
- SHA256:
- 958f3f74293a287ff0509ea8a9887435dd16ee0756f56af9ca3bfe9e1a5bb288
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