Text Classification
Transformers
PyTorch
English
distilbert
text
nlp
correction
text-embeddings-inference
Instructions to use wajidlinux99/gibberish-text-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wajidlinux99/gibberish-text-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wajidlinux99/gibberish-text-detector")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wajidlinux99/gibberish-text-detector") model = AutoModelForSequenceClassification.from_pretrained("wajidlinux99/gibberish-text-detector", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download sample_input.pkl from wajidlinux99/gibberish-text-detector: direct link, hf CLI and curl.
- Browser
- Download file 2.03 kB
-
https://huggingface.co/wajidlinux99/gibberish-text-detector/resolve/main/sample_input.pkl
- Command line
-
hf download hf://wajidlinux99/gibberish-text-detector/sample_input.pkl
-
curl -L -o sample_input.pkl https://huggingface.co/wajidlinux99/gibberish-text-detector/resolve/main/sample_input.pkl
2.03 kB
- Xet hash:
- 863eed0d9d5411628215d9c847ed10ad9cb133e59e9ee7bc96fedac547755415
- Size of remote file:
- 2.03 kB
- SHA256:
- be88e587f6b9b4ada6406c0ccb4d9a9eb199fb025cf4bb245d43e97662543603
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