Quyet 1.0

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LICENSE

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MANIFEST.sha256

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+d6949da46588e7fd54580ba8a9678d52c36c091d06baa6eab2a2f57513788f75  NOTICE
+f9e82ba0b6ebcb13515d844ec5452598c52e1436bb20db549a79dcb90e6b73fc  README.md
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NOTICE

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+Quyet by Chinh Nguyen
+Copyright 2026 Chinh Nguyen
+
+Licensed under the Apache License, Version 2.0 (see LICENSE). Redistributions of this work or of derivative works must keep this NOTICE, including the credit line above.
+
+This work includes or derives from:
+- ModernBERT-base by Answer.AI and LightOn (Apache-2.0): https://huggingface.co/answerdotai/ModernBERT-base (revision 8949b909ec90)
+
+The encoder models' option rendering and the refinement head of Quyet-1.0-Small follow Laya by Convai Innovations (https://huggingface.co/convaiinnovations/laya, Apache-2.0); this code was modified. No Laya weights are used.

README.md

@@ -0,0 +1,69 @@
+---
+license: apache-2.0
+library_name: quyet
+base_model: answerdotai/ModernBERT-base
+base_model_relation: finetune
+tags:
+- quyet
+- decision-model
+- calibrated
+- classification
+---
+
+# Quyet-1.0-Small-EN
+
+Quyet-1.0-Small-EN is a **decision model**: given a state (any text, JSON or conversation) and one or more typed questions, it picks one option per question and returns calibrated probabilities. Question types: `choice` (pick one label), `score` (an ordered scale) and `noul` (true / false). It is part of the Quyet 1.0 family (Large, Medium, Small, Small-EN, Tiny), released by Chinh Nguyen under Apache-2.0.
+
+| | |
+|---|---|
+| Base model | [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) |
+| Architecture | ModernBERT-base encoder + option-query head (cross-attention from each option into the state) |
+| Parameters | 153M |
+| Languages | English. Other languages work poorly. |
+| Input | 8,192 tokens |
+| Weights | 613 MB (F32) |
+| License | Apache-2.0 (see LICENSE and NOTICE) |
+
+## How to use
+
+```bash
+pip install quyet
+```
+
+```python
+import quyet
+
+m = quyet.load("chinhnc/Quyet-1.0-Small-EN")          # pip install quyet; downloads from Hugging Face
+r = m.predict(
+    {"message": "Please close my card, I lost it yesterday."},
+    {"intent": {"type": "choice", "instructions": "What does the customer want?",
+                 "criteria": {"cancel": "close the card", "limit": "change the limit", "other": None}},
+     "urgent": {"type": "noul", "instructions": "The request is urgent."},
+     "mood": {"type": "score", "instructions": "How upset is the customer?", "criteria": ["calm", "annoyed", "angry"]}},
+)
+print(r["answers"])   # {"intent": {"choice": ..., "confidence": ..., "probabilities": {...}}, "urgent": {"noul": P(true)}, ...}
+```
+
+Runs on CPU or any GPU. It reads the question, every option and the state in one pass (8,192 tokens) and scores each option; probabilities are temperature-calibrated per question type and option count.
+
+Answers follow the TypeSafe `/v1/systemone` shape: `choice` (with `probabilities`), `score` (expected level, `probabilities`, `legend`) and `noul` (P(true)). At most 10 options per question. Only the state is ever truncated: conversation lists keep their most recent turns, other states keep their beginning.
+
+## Credits
+
+- ModernBERT-base by Answer.AI and LightOn (Apache-2.0).
+- The option rendering follows Laya by Convai Innovations (Apache-2.0); no Laya weights are used.
+
+## Citation
+
+```bibtex
+@misc{quyet2026,
+  title  = {Quyet 1.0: calibrated decision models},
+  author = {Chinh Nguyen},
+  year   = {2026},
+  url    = {https://huggingface.co/chinhnc/Quyet-1.0-Small-EN}
+}
+```
+
+## License
+
+Apache-2.0. Keep the NOTICE file (it starts with "Quyet by Chinh Nguyen") when you redistribute this model or anything derived from it. Questions and issues: email@chinh.com.

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quyet_config.json

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+{
+ "quyet_format": 1,
+ "name": "Quyet-1.0-Small-EN",
+ "version": "1.0.0",
+ "kind": "encoder",
+ "head": "option_query_v1",
+ "max_len": 8192,
+ "temperatures": {
+  "choice:2": 5.2585,
+  "choice:3-5": 2.5551,
+  "choice:6-10": 1.6416,
+  "noul:2": 1.823,
+  "score:3-5": 2.1208
+ },
+ "encoder_config": {
+  "transformers_version": "5.17.0",
+  "architectures": [
+   "ModernBertForMaskedLM"
+  ],
+  "output_hidden_states": false,
+  "return_dict": true,
+  "dtype": "float32",
+  "chunk_size_feed_forward": 0,
+  "is_encoder_decoder": false,
+  "id2label": {
+   "0": "LABEL_0",
+   "1": "LABEL_1"
+  },
+  "label2id": {
+   "LABEL_0": 0,
+   "LABEL_1": 1
+  },
+  "problem_type": null,
+  "vocab_size": 50368,
+  "hidden_size": 768,
+  "intermediate_size": 1152,
+  "num_hidden_layers": 22,
+  "num_attention_heads": 12,
+  "hidden_activation": "gelu",
+  "max_position_embeddings": 8192,
+  "initializer_range": 0.02,
+  "initializer_cutoff_factor": 2.0,
+  "norm_eps": 1e-05,
+  "norm_bias": false,
+  "pad_token_id": 50283,
+  "eos_token_id": 50282,
+  "bos_token_id": 50281,
+  "cls_token_id": 50281,
+  "sep_token_id": 50282,
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "layer_types": [
+   "full_attention",
+   "sliding_attention",
+   "sliding_attention",
+   "full_attention",
+   "sliding_attention",
+   "sliding_attention",
+   "full_attention",
+   "sliding_attention",
+   "sliding_attention",
+   "full_attention",
+   "sliding_attention",
+   "sliding_attention",
+   "full_attention",
+   "sliding_attention",
+   "sliding_attention",
+   "full_attention",
+   "sliding_attention",
+   "sliding_attention",
+   "full_attention",
+   "sliding_attention",
+   "sliding_attention",
+   "full_attention"
+  ],
+  "rope_parameters": {
+   "sliding_attention": {
+    "rope_type": "default",
+    "rope_theta": 10000.0
+   },
+   "full_attention": {
+    "rope_type": "default",
+    "rope_theta": 160000.0
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+  "local_attention": 128,
+  "embedding_dropout": 0.0,
+  "mlp_bias": false,
+  "mlp_dropout": 0.0,
+  "decoder_bias": true,
+  "classifier_pooling": "mean",
+  "classifier_dropout": 0.0,
+  "classifier_bias": false,
+  "classifier_activation": "gelu",
+  "deterministic_flash_attn": false,
+  "sparse_prediction": false,
+  "sparse_pred_ignore_index": -100,
+  "tie_word_embeddings": true,
+  "global_attn_every_n_layers": 3,
+  "gradient_checkpointing": false,
+  "layer_norm_eps": 1e-05,
+  "model_type": "modernbert",
+  "position_embedding_type": "absolute",
+  "output_attentions": false
+ },
+ "base_model": {
+  "repo": "answerdotai/ModernBERT-base",
+  "revision": "8949b909ec900327062f0ebf497f51aef5e6f0c8",
+  "layers_kept": null
+ },
+ "source": {
+  "step": 24000,
+  "weights_sha256": "2a20d2cfba933c50e0f0f6ae957b6ed0693d2d6b34f3efd2305bd0ff6a786734"
+ }
+}

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