Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use evalstate/jim-crow-test2323 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use evalstate/jim-crow-test2323 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="evalstate/jim-crow-test2323")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("evalstate/jim-crow-test2323") model = AutoModelForSequenceClassification.from_pretrained("evalstate/jim-crow-test2323") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e8892ca28966a1344406289847aa80150ac5e46e38e75cabbd4cda6759f2cb1f
- Size of remote file:
- 5.33 kB
- SHA256:
- 35c53c8e387c3f08b6eae5055d897ac8dafbd289179ac9de1be19d95bf896903
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