Text Classification
Transformers
PyTorch
English
distilbert
distilbert-base-uncased-finetuned-sst-2-english
Instructions to use rosherd/job_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rosherd/job_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rosherd/job_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rosherd/job_classification") model = AutoModelForSequenceClassification.from_pretrained("rosherd/job_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from rosherd/job_classification: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/rosherd/job_classification/resolve/main/tokenizer.json
- Command line
-
hf download hf://rosherd/job_classification/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/rosherd/job_classification/resolve/main/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.