Instructions to use ybelkada/random-tiny-BertGenerationModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ybelkada/random-tiny-BertGenerationModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ybelkada/random-tiny-BertGenerationModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ybelkada/random-tiny-BertGenerationModel") model = AutoModel.from_pretrained("ybelkada/random-tiny-BertGenerationModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ybelkada/random-tiny-BertGenerationModel: direct link, hf CLI and curl.
- Browser
- Download file 497 kB
-
https://huggingface.co/ybelkada/random-tiny-BertGenerationModel/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ybelkada/random-tiny-BertGenerationModel/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ybelkada/random-tiny-BertGenerationModel/resolve/main/pytorch_model.bin
497 kB
- Xet hash:
- c74fe58f18237268a8f0845463c6da5699bf5b637c026eb869c28f9889d0162b
- Size of remote file:
- 497 kB
- SHA256:
- b4e15b1410300f3d68674d8f9938d35b18268f8cd94c9b118c9f4cb0cf8c2825
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