Text Classification
Transformers
Safetensors
English
Korean
Japanese
qev_decision_merged
feature-extraction
qev
typed-decision
custom-code
int8
custom_code
Instructions to use querypieai/QEV-9B-INT8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use querypieai/QEV-9B-INT8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="querypieai/QEV-9B-INT8", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("querypieai/QEV-9B-INT8", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from querypieai/QEV-9B-INT8: direct link, hf CLI and curl.
- Browser
- Download file 20 MB
-
https://huggingface.co/querypieai/QEV-9B-INT8/resolve/main/tokenizer.json
- Command line
-
hf download hf://querypieai/QEV-9B-INT8/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/querypieai/QEV-9B-INT8/resolve/main/tokenizer.json
20 MB
- Xet hash:
- b0cd6633e8692d4742e3f218f0c2ead37b0590db1a67a3e5b2f879d8d02d7fda
- Size of remote file:
- 20 MB
- SHA256:
- 1d8325caa17dffabd587f6eb025a642786caa785658d0d8c07b879dd1ea13477
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