Text Classification
Transformers
Safetensors
modernbert
anachronism-detection
abacus
provenance
Eval Results (legacy)
text-embeddings-inference
Instructions to use idirectships/abacus-cheat-tell-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use idirectships/abacus-cheat-tell-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="idirectships/abacus-cheat-tell-v3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("idirectships/abacus-cheat-tell-v3") model = AutoModelForSequenceClassification.from_pretrained("idirectships/abacus-cheat-tell-v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 07e31d7ed65e67cd9e8e45aea189a6d3df8db2b27ecbde479978e1f70913cd10
- Size of remote file:
- 5.2 kB
- SHA256:
- a1cf045808cc6471b62c074be2f41674e971f2b639987a7e498029f357d31584
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