Instructions to use marcosgg/bert-base-gl-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcosgg/bert-base-gl-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="marcosgg/bert-base-gl-cased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("marcosgg/bert-base-gl-cased") model = AutoModelForMaskedLM.from_pretrained("marcosgg/bert-base-gl-cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from marcosgg/bert-base-gl-cased: direct link, hf CLI and curl.
- Browser
- Download file 57 Bytes
-
https://huggingface.co/marcosgg/bert-base-gl-cased/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://marcosgg/bert-base-gl-cased/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/marcosgg/bert-base-gl-cased/resolve/main/tokenizer_config.json
57 Bytes
| {"do_lower_case": false, "tokenize_chinese_chars": false} |