Instructions to use hf-internal-testing/tiny-random-ModernBertForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ModernBertForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-ModernBertForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-ModernBertForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-ModernBertForMaskedLM") - Notebooks
- Google Colab
- Kaggle
Upload ONNX weights
Browse files- onnx/model.onnx +3 -0
onnx/model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:5e9fa083a8e9ac9c0f9fd8b9608f6984f273d391267c88549b8694567d997fd8
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size 6899781
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