Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Sifal/bertGED with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sifal/bertGED with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sifal/bertGED")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sifal/bertGED") model = AutoModelForSequenceClassification.from_pretrained("Sifal/bertGED", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sifal/bertGED: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/Sifal/bertGED/resolve/main/training_args.bin
- Command line
-
hf download hf://Sifal/bertGED/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sifal/bertGED/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- 0ec750f65410c6bbc19d628f7dadf60e86cd499759e3622dce52c26698c48e3d
- Size of remote file:
- 4.66 kB
- SHA256:
- 23829543593169706e5540658817bcc14e14793f341e583d257c2810ed0e7afc
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