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 validation.json from querypieai/QEV2-12B: direct link, hf CLI and curl.
- Browser
- Download file 537 Bytes
-
https://huggingface.co/querypieai/QEV2-12B/resolve/main/validation.json
- Command line
-
hf download hf://querypieai/QEV2-12B/validation.json
-
curl -L -o validation.json https://huggingface.co/querypieai/QEV2-12B/resolve/main/validation.json
537 Bytes
| { | |
| "status": "passed", | |
| "adapter_merged": true, | |
| "separate_adapter_distributed": false, | |
| "source_to_merged": { | |
| "max_probability_difference": 0.00600743293762207, | |
| "argmax_changed_questions": 0, | |
| "questions": 9 | |
| }, | |
| "serialized_reload_parity": { | |
| "max_probability_difference": 0.0, | |
| "argmax_changed_questions": 0, | |
| "questions": 9 | |
| }, | |
| "new_full_benchmark": false, | |
| "synthetic_questions": 9, | |
| "upload_performed": false, | |
| "original_source_weights_unchanged": true, | |
| "pointer_head_tokenizer_unchanged": true | |
| } | |