Text Classification
Transformers
Safetensors
English
qwen3
ai-text-detection
binary-classification
variable-position-readout
text-embeddings-inference
Instructions to use rasbt/ai-text-detector-qwen3-0.6b-variable with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rasbt/ai-text-detector-qwen3-0.6b-variable with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rasbt/ai-text-detector-qwen3-0.6b-variable")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rasbt/ai-text-detector-qwen3-0.6b-variable") model = AutoModelForSequenceClassification.from_pretrained("rasbt/ai-text-detector-qwen3-0.6b-variable", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7753dc6605f462c82c06afa22dbb9adbfd6a95b98aad6fbcc3486313d7d153c3
- Size of remote file:
- 11.4 MB
- SHA256:
- 4303dc9ca79e852acfbb69bdc65c23021bde2ef27124a96943967a3cc91030ad
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