Instructions to use regisss/bert-pretraining-gaudi-2-batch-size-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use regisss/bert-pretraining-gaudi-2-batch-size-32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="regisss/bert-pretraining-gaudi-2-batch-size-32")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("regisss/bert-pretraining-gaudi-2-batch-size-32") model = AutoModelForMaskedLM.from_pretrained("regisss/bert-pretraining-gaudi-2-batch-size-32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from regisss/bert-pretraining-gaudi-2-batch-size-32: direct link, hf CLI and curl.
- Browser
- Download file 541 MB
-
https://huggingface.co/regisss/bert-pretraining-gaudi-2-batch-size-32/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://regisss/bert-pretraining-gaudi-2-batch-size-32/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/regisss/bert-pretraining-gaudi-2-batch-size-32/resolve/main/pytorch_model.bin
541 MB
- Xet hash:
- 083d5f0460679a05758bc59331dae4486b53e8266edb34771f7c99f5965ca90a
- Size of remote file:
- 541 MB
- SHA256:
- 79ee8021e172b7485d56f1bc11cdce621748701dd739aca89d42fc465fce815b
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