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
File size: 858 Bytes
340ab69 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | {
"status": "passed",
"adapter_merged": true,
"separate_adapter_distributed": false,
"source_to_merged": {
"max_probability_difference": 0.0010743141174316406,
"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,
"source_to_merged_int8": {
"max_probability_difference": 0.0061776041984558105,
"argmax_changed_questions": 0,
"questions": 9
},
"merged_bf16_to_int8": {
"max_probability_difference": 0.00510329008102417,
"argmax_changed_questions": 0,
"questions": 9
},
"quantized_linear_count": 248,
"original_source_weights_unchanged": true,
"pointer_head_tokenizer_unchanged": true
}
|