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 tokenizer.json from querypieai/QEV2-12B: direct link, hf CLI and curl.
- Browser
- Download file 32.2 MB
-
https://huggingface.co/querypieai/QEV2-12B/resolve/main/tokenizer.json
- Command line
-
hf download hf://querypieai/QEV2-12B/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/querypieai/QEV2-12B/resolve/main/tokenizer.json
32.2 MB
- Xet hash:
- afb80ad0905955585975c922e4c132b12f0b0533c1d9f0ae1798a2f4dceec39c
- Size of remote file:
- 32.2 MB
- SHA256:
- 3151898c022536cf420b732dd2fcbf8e7c456cd39711a27f9b82a7ced72b6c83
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