Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use tbochens/test-train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tbochens/test-train with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tbochens/test-train")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tbochens/test-train") model = AutoModelForSequenceClassification.from_pretrained("tbochens/test-train", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2646bbe7e5ae3e7cc105c220aa9d6147aa567e6e23df716b2f0888cbff515a83
- Size of remote file:
- 438 MB
- SHA256:
- a92789e8a2bfea66129b9603c56d8517e41bf94a6f6e4b0024aec9a9cd5454ab
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