Instructions to use johnpaulbin/gibberish-detector-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Model2Vec
How to use johnpaulbin/gibberish-detector-tiny with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("johnpaulbin/gibberish-detector-tiny") embeddings = model.encode(["It's dangerous to go alone!", "It's a secret to everybody."]) print(embeddings.shape) - sentence-transformers
How to use johnpaulbin/gibberish-detector-tiny with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("johnpaulbin/gibberish-detector-tiny") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from johnpaulbin/gibberish-detector-tiny: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/johnpaulbin/gibberish-detector-tiny/resolve/main/tokenizer.json
- Command line
-
hf download hf://johnpaulbin/gibberish-detector-tiny/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/johnpaulbin/gibberish-detector-tiny/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 139136db2b5c557005e3c8018093a2bce5be5db0027e303954f9f192b6ea8bfd
- Size of remote file:
- 17.1 MB
- SHA256:
- 249df0778f236f6ece390de0de746838ef25b9d6954b68c2ee71249e0a9d8fd4
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