Text Classification
Transformers
Safetensors
English
Turkish
German
qwen3_5
image-text-to-text
decision-model
calibration
conformal-prediction
uncertainty
reasoning
routing
triage
jev
typesafe
qwen3.5
english
Instructions to use mertkayacs/Deem-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mertkayacs/Deem-4B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mertkayacs/Deem-4B")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("mertkayacs/Deem-4B") model = AutoModelForMultimodalLM.from_pretrained("mertkayacs/Deem-4B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
calibration fitted on the held-out calibration splits
Browse files- calibration.json +90 -0
calibration.json
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{
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"temperatures": {
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"default": 1.1004,
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"noul": 1.0717,
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"choice": 1.1145,
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"score": 1.0696,
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"noul:en": 1.0431,
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"choice:en": 1.0508,
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"score:en": 1.0321,
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"choice:tr": 1.1628,
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"noul:tr": 1.0814,
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"choice:de": 1.1331,
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"noul:de": 1.1025
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},
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"fitted_on": 3224,
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"min_group": 150,
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"conformal": {
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"choice": {
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"0.8": 0.2753,
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"0.9": 0.505204,
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"0.95": 0.776256
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},
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"choice:en": {
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"0.8": 0.293443,
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"0.9": 0.495969,
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"0.95": 0.708513
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},
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"default": {
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"0.8": 0.370846,
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"0.9": 0.564361,
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"0.95": 0.776256
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},
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"score": {
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"0.8": 0.535527,
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"0.9": 0.66665,
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"0.95": 0.818577
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},
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"score:en": {
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"0.8": 0.518117,
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"0.9": 0.604395,
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"0.95": 0.678569
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},
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"choice:tr": {
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"0.8": 0.335178,
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"0.9": 0.6314,
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"0.95": 0.844323
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},
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"choice:de": {
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"0.8": 0.204405,
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"0.9": 0.364523,
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"0.95": 0.635809
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}
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},
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"auto_threshold": {
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"choice": 0.5,
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"noul": 0.0,
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"score": 0.0
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},
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"auto_fit": {
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"choice": {
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"threshold": 0.5,
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"accuracy_off": 0.9014,
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"accuracy_auto": 0.9296,
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"accuracy_on": 0.9155,
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"reasoning_share": 0.1268,
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"pairs": 71
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},
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"noul": {
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"threshold": 0.0,
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"accuracy_off": 0.9464,
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"accuracy_auto": 0.9464,
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"accuracy_on": 0.8929,
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"reasoning_share": 0.0,
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"pairs": 56
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},
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"score": {
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"threshold": 0.0,
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"accuracy_off": 0.8421,
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"accuracy_auto": 0.8421,
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"accuracy_on": 0.8421,
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"reasoning_share": 0.0,
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"pairs": 19
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}
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},
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"fit": {
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"suite": "data/splits/v2/calib-all.jsonl",
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"decisions": 3224,
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"date": "2026-10-01"
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}
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}
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