Instructions to use Ghunghru/xmod-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ghunghru/xmod-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ghunghru/xmod-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ghunghru/xmod-base") model = AutoModelForSequenceClassification.from_pretrained("Ghunghru/xmod-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Ghunghru/xmod-base: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/Ghunghru/xmod-base/resolve/main/training_args.bin
- Command line
-
hf download hf://Ghunghru/xmod-base/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Ghunghru/xmod-base/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- de015830b6c1590be3e32b8e7d4862c6fdafbd9c6770bde06b9374a6350f6172
- Size of remote file:
- 4.54 kB
- SHA256:
- c899e786d3b65088b96c22ce885713053538816c577b391773ce0c0eebfdb805
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