Text Classification
Transformers
ONNX
Safetensors
bert
social-media
content-filtering
engagement-bait
distillation
text-embeddings-inference
Instructions to use selftaughtdev/engagement-farm-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use selftaughtdev/engagement-farm-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="selftaughtdev/engagement-farm-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("selftaughtdev/engagement-farm-classifier") model = AutoModelForSequenceClassification.from_pretrained("selftaughtdev/engagement-farm-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 216 Bytes
76c28a4 | 1 2 3 4 5 6 7 8 9 | {
"eval_loss": 0.17980128526687622,
"eval_accuracy": 0.972972972972973,
"eval_f1": 0.9433962264150944,
"eval_runtime": 2.8042,
"eval_samples_per_second": 277.086,
"eval_steps_per_second": 4.636,
"epoch": 6.0
} |