Instructions to use bertin-project/bertin-base-random with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bertin-project/bertin-base-random with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="bertin-project/bertin-base-random")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("bertin-project/bertin-base-random") model = AutoModelForMaskedLM.from_pretrained("bertin-project/bertin-base-random", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from bertin-project/bertin-base-random: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/bertin-project/bertin-base-random/resolve/754d33bc2bb3227fc4e61cf4151b4bfbbc30986f/pytorch_model.bin
- Command line
-
hf download hf://bertin-project/bertin-base-random@754d33bc2bb3227fc4e61cf4151b4bfbbc30986f/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/bertin-project/bertin-base-random/resolve/754d33bc2bb3227fc4e61cf4151b4bfbbc30986f/pytorch_model.bin
499 MB
- Xet hash:
- e33175ce48783b83f22857de535e1270087af0d5fa9cb59575b336029d79d3aa
- Size of remote file:
- 499 MB
- SHA256:
- 05418d983f3a406a0c8fc7aadf699145571d2f8f80304209847fcb512c851801
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