Text Classification
Transformers
TensorBoard
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use selsar/target-abroad-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use selsar/target-abroad-de with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="selsar/target-abroad-de")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("selsar/target-abroad-de") model = AutoModelForSequenceClassification.from_pretrained("selsar/target-abroad-de", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download threshold_selection.json from selsar/target-abroad-de: direct link, hf CLI and curl.
- Browser
- Download file 143 Bytes
-
https://huggingface.co/selsar/target-abroad-de/resolve/main/threshold_selection.json
- Command line
-
hf download hf://selsar/target-abroad-de/threshold_selection.json
-
curl -L -o threshold_selection.json https://huggingface.co/selsar/target-abroad-de/resolve/main/threshold_selection.json
143 Bytes
| { | |
| "best_threshold": 0.9, | |
| "validation_stats": { | |
| "precision": 0.8296296296296296, | |
| "recall": 0.896, | |
| "f1": 0.8615384615384616 | |
| } | |
| } |