Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use HAriGa/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HAriGa/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HAriGa/my_awesome_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HAriGa/my_awesome_model") model = AutoModelForSequenceClassification.from_pretrained("HAriGa/my_awesome_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 65f81da3ab6317ede13f19b23d44b70a785e918b7ffab52abde8e340be637c00
- Size of remote file:
- 3.52 kB
- SHA256:
- 4808a7a23502dd5120f9370fb5823f3061c3e187826d1b703c50cf0396a96c20
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