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")# pip install -U transformers accelerate # 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 flax_model.msgpack from GottBERT/GottBERT_base_last: direct link, hf CLI and curl.
- Browser
- Download file 504 MB
-
https://huggingface.co/GottBERT/GottBERT_base_last/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://GottBERT/GottBERT_base_last/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/GottBERT/GottBERT_base_last/resolve/main/flax_model.msgpack
504 MB
- Xet hash:
- cf3c67abeb5e4c3a992562301e732229cdb9dceba6f00293a19c4a8c863538cd
- Size of remote file:
- 504 MB
- SHA256:
- 07ae69e926319c274d3c745a9f9733d9f8dfd2b7ba4a6eec5d5e8fc182b830e4
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