Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use evalstate/jim-crow-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use evalstate/jim-crow-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="evalstate/jim-crow-test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("evalstate/jim-crow-test") model = AutoModelForSequenceClassification.from_pretrained("evalstate/jim-crow-test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a4a5064bae09f3da791f679c06216096cf5a6b27bc7092ec86c301cfb0b21e38
- Size of remote file:
- 5.27 kB
- SHA256:
- 59039213c71676876cfcb2e89f52f82d7554ba1d1fd0fa40d0ae5181826b27e9
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