Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use TARGAZ/test_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TARGAZ/test_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TARGAZ/test_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TARGAZ/test_model") model = AutoModelForSequenceClassification.from_pretrained("TARGAZ/test_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a7fd53e92815a5218e91120e0e9fee13917233f28b7c01ec1008eceb39451b3
- Size of remote file:
- 499 MB
- SHA256:
- 4f2313d9d544d252d805101dd7166fe360146d1e88df124bbc85a1951e85e68f
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