Instructions to use GottBERT/GottBERT_base_last with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GottBERT/GottBERT_base_last with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="GottBERT/GottBERT_base_last")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("GottBERT/GottBERT_base_last") model = AutoModelForMaskedLM.from_pretrained("GottBERT/GottBERT_base_last", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from GottBERT/GottBERT_base_last: direct link, hf CLI and curl.
- Browser
- Download file 507 MB
-
https://huggingface.co/GottBERT/GottBERT_base_last/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://GottBERT/GottBERT_base_last/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/GottBERT/GottBERT_base_last/resolve/main/pytorch_model.bin
507 MB
- Xet hash:
- b24dfb88da5891698e17f5d5f1e56f6d3af53ae99dd3222ef08d6e5d5c206857
- Size of remote file:
- 507 MB
- SHA256:
- 99ecf9324fe71505053e6a9135d3ce631204f5b4d68e98e39dd401ed4a6d3497
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