Instructions to use Andrei95/jobbert-skill with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Andrei95/jobbert-skill with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Andrei95/jobbert-skill")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Andrei95/jobbert-skill") model = AutoModelForTokenClassification.from_pretrained("Andrei95/jobbert-skill", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Andrei95/jobbert-skill: direct link, hf CLI and curl.
- Browser
- Download file 669 kB
-
https://huggingface.co/Andrei95/jobbert-skill/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://Andrei95/jobbert-skill@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Andrei95/jobbert-skill/resolve/refs%2Fpr%2F1/tokenizer.json
669 kB
- Xet hash:
- d1c4637e940ab8ef8a1d7f87ec6e82cba32275b0d382668239707890f6035a03
- Size of remote file:
- 669 kB
- SHA256:
- f418a7993537e03eb4a3c3a3f494822448307ac249837f87bff3548992013da5
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