Instructions to use ydshieh/tiny-random-BertModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ydshieh/tiny-random-BertModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ydshieh/tiny-random-BertModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ydshieh/tiny-random-BertModel") model = AutoModel.from_pretrained("ydshieh/tiny-random-BertModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ydshieh/tiny-random-BertModel: direct link, hf CLI and curl.
- Browser
- Download file 382 kB
-
https://huggingface.co/ydshieh/tiny-random-BertModel/resolve/refs%2Fpr%2F4/pytorch_model.bin
- Command line
-
hf download hf://ydshieh/tiny-random-BertModel@refs/pr/4/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ydshieh/tiny-random-BertModel/resolve/refs%2Fpr%2F4/pytorch_model.bin
382 kB
- Xet hash:
- 4cd35d3d75b0c40090966c58f88d6f907d10647af4ad23e170d69a3bd983da7c
- Size of remote file:
- 382 kB
- SHA256:
- d16b8e6984ae6b48c6b1b2f98d7d62f25ecbca5d3e7bccc053167a140bdae22c
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