Instructions to use peft-internal-testing/tiny-random-BertModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peft-internal-testing/tiny-random-BertModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="peft-internal-testing/tiny-random-BertModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("peft-internal-testing/tiny-random-BertModel") model = AutoModel.from_pretrained("peft-internal-testing/tiny-random-BertModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from peft-internal-testing/tiny-random-BertModel: direct link, hf CLI and curl.
- Browser
- Download file 361 kB
-
https://huggingface.co/peft-internal-testing/tiny-random-BertModel/resolve/main/model.safetensors
- Command line
-
hf download hf://peft-internal-testing/tiny-random-BertModel/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/peft-internal-testing/tiny-random-BertModel/resolve/main/model.safetensors
361 kB
- Xet hash:
- ad0bfc96ea9167d84a9c49ebedd7fdad77118203b427b5df31156c0b06e1cfbe
- Size of remote file:
- 361 kB
- SHA256:
- 4e011b7f1af1d32895c6f1e5ea228e0aa05b826225c467b8de805cef0ad6b994
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