Instructions to use deepset/gbert-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/gbert-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="deepset/gbert-large")# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("deepset/gbert-large", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from deepset/gbert-large: direct link, hf CLI and curl.
- Browser
- Download file 83 Bytes
-
https://huggingface.co/deepset/gbert-large/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://deepset/gbert-large/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/deepset/gbert-large/resolve/main/tokenizer_config.json
83 Bytes
| {"do_lower_case": false, "max_len": 512, "init_inputs": [], "strip_accents":false} | |