Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use savioteless/test_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use savioteless/test_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="savioteless/test_trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("savioteless/test_trainer") model = AutoModelForSequenceClassification.from_pretrained("savioteless/test_trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c984b91dcbf772f4b0e897bc79f834ad41e0615e54203dc4b21cdb529f06a577
- Size of remote file:
- 4.6 kB
- SHA256:
- e1e64dd4fc157aecba028ed22f248367d582f32367bceeeacda245f9d1fa2656
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.