Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use xysmalobia/test-trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xysmalobia/test-trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xysmalobia/test-trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xysmalobia/test-trainer") model = AutoModelForSequenceClassification.from_pretrained("xysmalobia/test-trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6eb599145c2447f63c1f7340b8b4a49ae9d1e3ba5aa42e2e6009cf1f8ded649c
- Size of remote file:
- 438 MB
- SHA256:
- e4867d25d4d9b2f5ba84d4c2e3b693bcf9f4d0962dbfd34553d778aca7092eca
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