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")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ghunghru/xmod-base") model = AutoModelForSequenceClassification.from_pretrained("Ghunghru/xmod-base") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:fee8c6504aee915f0288d7be6589be87f07c3a6d3e52f9c9afba82977b856721
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size 3410460344
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