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 tokenizer.json from Ghunghru/xmod-base: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/Ghunghru/xmod-base/resolve/main/tokenizer.json
- Command line
-
hf download hf://Ghunghru/xmod-base/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Ghunghru/xmod-base/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- c0bf722a05d8ac699f8f0b46f633ef386ed01d038423ec1f7fd9ea72cdd9600a
- Size of remote file:
- 17.1 MB
- SHA256:
- 96628b7704b1f281a45df5d9feb0ef79e2c058130bf55a20bedd465146416746
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