Text Classification
Transformers
ONNX
Safetensors
GLiClass
rlcd
typesafe-ai
jev
decision-engine
system-1
modernbert
gliclass
non-autoregressive
zero-token-generation
structured-outputs
calibration
expected-calibration-error
ece
brier-score
proper-scoring-rules
webgpu
edge-ai
fast-inference
banking77
Instructions to use heman10x/rlcd-modernbert-151m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use heman10x/rlcd-modernbert-151m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="heman10x/rlcd-modernbert-151m")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("heman10x/rlcd-modernbert-151m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "model_id": "openjev-modernbert-151.4m", | |
| "temperature": 2.8039, | |
| "log_temperature": 1.0309995577626943, | |
| "scope": "open_domain_calibrated_v1", | |
| "per_k": { | |
| "2": 5.0069, | |
| "3": 5.0069, | |
| "4": 4.0314, | |
| "5": 3.0560, | |
| "6": 2.3898, | |
| "7": 2.3898, | |
| "9": 1.6668, | |
| "11": 3.3919, | |
| "17": 1.7200, | |
| "25": 1.5144 | |
| }, | |
| "artifact_hash": "b4742a033bce3fb4707e78d910dc89d53c30656d028b1836a992ba87e0766324", | |
| "format_version": "rlcd-calibrator-v1", | |
| "provenance": { | |
| "fitted_on": [ | |
| "data/real_banking_cal.jsonl", | |
| "data/synthetic_calibration.jsonl", | |
| "data/slice_cardinality_k3.jsonl", | |
| "data/slice_cardinality_k5.jsonl", | |
| "data/slice_cardinality_k9.jsonl", | |
| "data/slice_cardinality_k17.jsonl", | |
| "data/slice_cardinality_k25.jsonl", | |
| "data/slice_distant_oos.jsonl", | |
| "data/slice_missing_option.jsonl", | |
| "data/gen/T01.jsonl", | |
| "data/gen/T02.jsonl", | |
| "data/gen/T03.jsonl", | |
| "data/gen/T07.jsonl", | |
| "data/gen/T12.jsonl" | |
| ], | |
| "total_calibration_items": 1753, | |
| "date": "2026-09-20T14:00:00Z", | |
| "notes": "Honest stratified temperature scaling fitted strictly via NLL minimization on held-out calibration data. Zero fitting on JevBench evaluation tasks." | |
| } | |
| } |