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%2F3/pytorch_model.bin
- Command line
-
hf download hf://ydshieh/tiny-random-BertModel@refs/pr/3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ydshieh/tiny-random-BertModel/resolve/refs%2Fpr%2F3/pytorch_model.bin
382 kB
- Xet hash:
- 6a3fbffa5980b40cf206014f919aacf767e81ffddeef0782fba6720b2a5d8864
- Size of remote file:
- 382 kB
- SHA256:
- ebd1699d694162c0980406672a7fa0dbdc77c2adc0fd040ea797e7cf0b750b7e
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