Instructions to use worldbank/jobless-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use worldbank/jobless-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="worldbank/jobless-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("worldbank/jobless-bert") model = AutoModelForSequenceClassification.from_pretrained("worldbank/jobless-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from worldbank/jobless-bert: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/worldbank/jobless-bert/resolve/main/training_args.bin
- Command line
-
hf download hf://worldbank/jobless-bert/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/worldbank/jobless-bert/resolve/main/training_args.bin
3.52 kB
- Xet hash:
- 4d080526e55773845085c34ce620d963877cf49290acb8f9abeb28ceb47d01a4
- Size of remote file:
- 3.52 kB
- SHA256:
- fa4d305348bbdab5ce00483498c9da7bcb3a6e677353c3debbecbb4a0b58f077
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