Text Classification
Transformers
PyTorch
Safetensors
French
deberta-v2
lm-detection
Eval Results (legacy)
text-embeddings-inference
Instructions to use almanach/camemberta-chatgptdetect-noisy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use almanach/camemberta-chatgptdetect-noisy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="almanach/camemberta-chatgptdetect-noisy")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("almanach/camemberta-chatgptdetect-noisy") model = AutoModelForSequenceClassification.from_pretrained("almanach/camemberta-chatgptdetect-noisy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from almanach/camemberta-chatgptdetect-noisy: direct link, hf CLI and curl.
- Browser
- Download file 450 MB
-
https://huggingface.co/almanach/camemberta-chatgptdetect-noisy/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://almanach/camemberta-chatgptdetect-noisy/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/almanach/camemberta-chatgptdetect-noisy/resolve/main/pytorch_model.bin
450 MB
- Xet hash:
- caaca87c09dc106e35d23597ed4d2089ca33ed6e073cc6843cc350565f2ec802
- Size of remote file:
- 450 MB
- SHA256:
- 3df46270b7f4bf089fed33b7d70799374213fa6f33406b8c09884f91c93bcdaa
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