Instructions to use CleveGreen/JobClassifier_v3_gpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CleveGreen/JobClassifier_v3_gpt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CleveGreen/JobClassifier_v3_gpt")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CleveGreen/JobClassifier_v3_gpt") model = AutoModelForSequenceClassification.from_pretrained("CleveGreen/JobClassifier_v3_gpt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from CleveGreen/JobClassifier_v3_gpt: direct link, hf CLI and curl.
- Browser
- Download file 511 MB
-
https://huggingface.co/CleveGreen/JobClassifier_v3_gpt/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://CleveGreen/JobClassifier_v3_gpt/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/CleveGreen/JobClassifier_v3_gpt/resolve/main/pytorch_model.bin
511 MB
- Xet hash:
- 9c1d46274de660b2d4456bb006048f3cd2b0e059221f98b3512cacce15fda6b7
- Size of remote file:
- 511 MB
- SHA256:
- adbbb1c9c080dfeb834456e451e68d344a067a662e9ed528e253fe1ec4172df2
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