Text Classification
Transformers
Safetensors
eurobert
commit-messages
humor-detection
lora
git
optuna-optimized
custom_code
Eval Results (legacy)
Instructions to use LBerthalon/eurobert-commit-humor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LBerthalon/eurobert-commit-humor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LBerthalon/eurobert-commit-humor", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LBerthalon/eurobert-commit-humor", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("LBerthalon/eurobert-commit-humor", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
🚀 Upload du modèle optimisé avec Optuna (85.3% accuracy globale, 82.9% funny accuracy)
02bdefc verified Download threshold.json from LBerthalon/eurobert-commit-humor: direct link, hf CLI and curl.
- Browser
- Download file 31 Bytes
-
https://huggingface.co/LBerthalon/eurobert-commit-humor/resolve/main/threshold.json
- Command line
-
hf download hf://LBerthalon/eurobert-commit-humor/threshold.json
-
curl -L -o threshold.json https://huggingface.co/LBerthalon/eurobert-commit-humor/resolve/main/threshold.json
31 Bytes
| { | |
| "funny_threshold": 0.35 | |
| } |