Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use rach405/test_trainer3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rach405/test_trainer3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rach405/test_trainer3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rach405/test_trainer3") model = AutoModelForSequenceClassification.from_pretrained("rach405/test_trainer3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 82d92f4f86fb4e40634e50f3ca2060ab3f65b903f52ef971d4fb8d20472da731
- Size of remote file:
- 2.99 kB
- SHA256:
- afe6a35d248074811ad658c7aa81d3674c2fe9c0d05592216f2cbd11a873da9e
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