Instructions to use hf-internal-testing/tiny-random-SqueezeBertModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SqueezeBertModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-SqueezeBertModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-SqueezeBertModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-SqueezeBertModel") - 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 sha256:719a0e4b994c95bb00015a739514d6487b27d0959d1b36f188eec6ee1a73699f
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size 326592
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