Text Classification
Transformers
Safetensors
English
Korean
Japanese
qev_decision_merged
feature-extraction
qev
typed-decision
custom-code
bf16
custom_code
Instructions to use querypieai/QEV-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use querypieai/QEV-9B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="querypieai/QEV-9B", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("querypieai/QEV-9B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from querypieai/QEV-9B: direct link, hf CLI and curl.
- Browser
- Download file 745 Bytes
-
https://huggingface.co/querypieai/QEV-9B/resolve/main/config.json
- Command line
-
hf download hf://querypieai/QEV-9B/config.json
-
curl -L -o config.json https://huggingface.co/querypieai/QEV-9B/resolve/main/config.json
745 Bytes
| { | |
| "model_type": "qev_decision_merged", | |
| "architectures": [ | |
| "QevDecisionModel" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_qev_public.QevPublicDecisionConfig", | |
| "AutoModel": "modeling_qev_public.QevDecisionModel" | |
| }, | |
| "display_name": "QEV-9B", | |
| "precision": "bf16", | |
| "family": "qwen", | |
| "hidden_size": 4096, | |
| "pointer_dim": 256, | |
| "pointer_dropout": 0.0, | |
| "temperature": 1.25594321575479, | |
| "encoding_profile": "legacy", | |
| "scoring_mode": "pointer", | |
| "backbone_forward": "direct", | |
| "max_state": 2048, | |
| "max_branch": 2688, | |
| "max_packed": 10752, | |
| "base_model": "Qwen/Qwen3.5-9B-Base", | |
| "base_model_revision": "68c46c4b3498877f3ef123c856ecfde50c39f404", | |
| "adapter_merged": true, | |
| "distribution": "inference-only" | |
| } | |