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")# pip install -U transformers accelerate # 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
Download training_args.bin from TARGAZ/test_model: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/TARGAZ/test_model/resolve/main/training_args.bin
- Command line
-
hf download hf://TARGAZ/test_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/TARGAZ/test_model/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- cef9ccf9fa4b776592691359b12a69dde1a4ffe177feb0574fc3626e567b9f23
- Size of remote file:
- 5.3 kB
- SHA256:
- 610bd1d791217d198dc8b9ced9e5719f14d80b06f4fcd657e771bdd8d7448029
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