Instructions to use CleveGreen/JobClassifier_v2_gpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CleveGreen/JobClassifier_v2_gpt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CleveGreen/JobClassifier_v2_gpt")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CleveGreen/JobClassifier_v2_gpt") model = AutoModelForSequenceClassification.from_pretrained("CleveGreen/JobClassifier_v2_gpt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from CleveGreen/JobClassifier_v2_gpt: direct link, hf CLI and curl.
- Browser
- Download file 511 MB
-
https://huggingface.co/CleveGreen/JobClassifier_v2_gpt/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://CleveGreen/JobClassifier_v2_gpt/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/CleveGreen/JobClassifier_v2_gpt/resolve/main/pytorch_model.bin
511 MB
- Xet hash:
- 2ab16ffca4d81bb2666953131abfccc47add4666832ab5fe82735e0abdd81501
- Size of remote file:
- 511 MB
- SHA256:
- 1029585f10c4291d0905326d07caafbe059f4ad0944dc57d494cd44b8965ad3d
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