Instructions to use peanutacake/ajmc_ner_de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peanutacake/ajmc_ner_de with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="peanutacake/ajmc_ner_de")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("peanutacake/ajmc_ner_de") model = AutoModelForTokenClassification.from_pretrained("peanutacake/ajmc_ner_de", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from peanutacake/ajmc_ner_de: direct link, hf CLI and curl.
- Browser
- Download file 729 kB
-
https://huggingface.co/peanutacake/ajmc_ner_de/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://peanutacake/ajmc_ner_de@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/peanutacake/ajmc_ner_de/resolve/refs%2Fpr%2F1/tokenizer.json
729 kB
- Xet hash:
- 69f0e8738325b0c49affab68e455eda40884e1d898bd4b803ff92f0f37f276e7
- Size of remote file:
- 729 kB
- SHA256:
- f3da22011dac9fd48c033ea174c477e544f8c791754a73bcf225b3ed6ca2d45c
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