Instructions to use Ghunghru/gbert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ghunghru/gbert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ghunghru/gbert-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ghunghru/gbert-base") model = AutoModelForSequenceClassification.from_pretrained("Ghunghru/gbert-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Ghunghru/gbert-base: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/Ghunghru/gbert-base/resolve/main/training_args.bin
- Command line
-
hf download hf://Ghunghru/gbert-base/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Ghunghru/gbert-base/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 6edc1bb387f36c91b64fb848130a2d93005b997e676254928f2587b93061392a
- Size of remote file:
- 4.54 kB
- SHA256:
- ddeda7b41cf9b752cb0a1a7dc29b85b9442ac06446d565c2f8f16a442abc2642
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