Text Classification
Transformers
Safetensors
English
Korean
Japanese
qev_decision_merged
feature-extraction
qev
typed-decision
custom-code
bf16
custom_code
Instructions to use querypieai/QEV2-12B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use querypieai/QEV2-12B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="querypieai/QEV2-12B", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("querypieai/QEV2-12B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download evaluation.json from querypieai/QEV2-12B: direct link, hf CLI and curl.
- Browser
- Download file 645 Bytes
-
https://huggingface.co/querypieai/QEV2-12B/resolve/main/evaluation.json
- Command line
-
hf download hf://querypieai/QEV2-12B/evaluation.json
-
curl -L -o evaluation.json https://huggingface.co/querypieai/QEV2-12B/resolve/main/evaluation.json
645 Bytes
| { | |
| "historical_metrics": { | |
| "mmlu": 0.4368896484375, | |
| "belebele": 0.688936723255625, | |
| "private": 0.9185185185185185, | |
| "composite": 0.6814482967372145, | |
| "dlp_accuracy": 0.9829491632459741, | |
| "dlp_recall": 0.9968774395003903, | |
| "dlp_f2": 0.9897690280576655, | |
| "dlp_fp": 50, | |
| "dlp_fn": 4 | |
| }, | |
| "new_full_benchmark": false, | |
| "counts": { | |
| "mmlu": 16384, | |
| "belebele": 24622, | |
| "private": 540, | |
| "dlp": 3167 | |
| }, | |
| "dlp_threshold": 0.5, | |
| "context": { | |
| "state": 384, | |
| "branch": 1024, | |
| "packed": 2048 | |
| }, | |
| "scope": "Historical unmerged BF16 source only; NOT newly measured merged/INT8 benchmark scores" | |
| } | |