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 tf_model.h5 from ydshieh/tiny-random-BertModel: direct link, hf CLI and curl.
- Browser
- Download file 472 kB
-
https://huggingface.co/ydshieh/tiny-random-BertModel/resolve/main/tf_model.h5
- Command line
-
hf download hf://ydshieh/tiny-random-BertModel/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/ydshieh/tiny-random-BertModel/resolve/main/tf_model.h5
472 kB
- Xet hash:
- 3788f4f1a8ff4f0c2dc97aa3ff1ab50873e2e08299760967030a8d04ce154167
- Size of remote file:
- 472 kB
- SHA256:
- 47a32af752b06f1c76c257d645b15d32baa64e3052f1aed4f220de8539949074
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