Instructions to use CleveGreen/JobClassifier_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CleveGreen/JobClassifier_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CleveGreen/JobClassifier_v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CleveGreen/JobClassifier_v2") model = AutoModelForSequenceClassification.from_pretrained("CleveGreen/JobClassifier_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from CleveGreen/JobClassifier_v2: direct link, hf CLI and curl.
- Browser
- Download file 434 MB
-
https://huggingface.co/CleveGreen/JobClassifier_v2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://CleveGreen/JobClassifier_v2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/CleveGreen/JobClassifier_v2/resolve/main/pytorch_model.bin
434 MB
- Xet hash:
- 0692b7cc5a51d0cc46280e3d1bc462290189fd98795f27d848dc4862c62c2948
- Size of remote file:
- 434 MB
- SHA256:
- 74ad669d10ef9ba1afac4ac13e6141c7aeed46cfc1ebb496b75d4ba23430dcd5
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