Instructions to use ikim-uk-essen/geberta-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ikim-uk-essen/geberta-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ikim-uk-essen/geberta-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ikim-uk-essen/geberta-large") model = AutoModelForMaskedLM.from_pretrained("ikim-uk-essen/geberta-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from ikim-uk-essen/geberta-large: direct link, hf CLI and curl.
- Browser
- Download file 22 Bytes
-
https://huggingface.co/ikim-uk-essen/geberta-large/resolve/main/added_tokens.json
- Command line
-
hf download hf://ikim-uk-essen/geberta-large/added_tokens.json
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curl -L -o added_tokens.json https://huggingface.co/ikim-uk-essen/geberta-large/resolve/main/added_tokens.json
22 Bytes
| { | |
| "[MASK]": 50265 | |
| } | |