Instructions to use bassie96code/RobBERT-LLM-wettekst with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bassie96code/RobBERT-LLM-wettekst with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="bassie96code/RobBERT-LLM-wettekst")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("bassie96code/RobBERT-LLM-wettekst") model = AutoModelForTokenClassification.from_pretrained("bassie96code/RobBERT-LLM-wettekst", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from bassie96code/RobBERT-LLM-wettekst: direct link, hf CLI and curl.
- Browser
- Download file 1.83 MB
-
https://huggingface.co/bassie96code/RobBERT-LLM-wettekst/resolve/main/tokenizer.json
- Command line
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hf download hf://bassie96code/RobBERT-LLM-wettekst/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/bassie96code/RobBERT-LLM-wettekst/resolve/main/tokenizer.json
1.83 MB
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