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---
license: apache-2.0
language:
- kk
- ru
- en
tags:
- qwen3
- kazakh
- dare-ties
- merge
- noesis
- dhcf-fno
- 600m
base_model:
- ekitil/ekitil-core-qwen3-600m-kkru-base-v1
- ekitil/ekitil-qwen3-600m-kk
- ekitil/ekitil-qwen3-600m-kkru
pipeline_tag: text-generation
---
# NOESIS-Qwen3-0.6B-Darwin-Ekitil-Sozkz-KZ-BF16
**DARE-TIES merge of three Kazakh/Russian Qwen3-600M models, producing a stronger KK/RU specialist.**
Released as part of the **NOESIS Professional Multilingual Dubbing Automation Platform**
(framework: DHCF-FNO -- Deterministic Hybrid Control Framework for Frozen Neural Operators).
- **Founder:** Ilia Bolotnikov
- **Organization:** [AMAImedia.com](https://www.amaimedia.com)
- **X (Twitter):** [@AMAImediacom](https://x.com/AMAImediacom)
- **LinkedIn:** [Ilia Bolotnikov](https://www.linkedin.com/in/ilia-bolotnikov)
- **Telegram:** [@djbionicl](https://t.me/djbionicl)
- **NOESIS version:** v14.7
- **Release date:** 2026-04
---
## Model summary
| Property | Value |
| --- | --- |
| Architecture | `Qwen3ForCausalLM` |
| Parameters | ~600M |
| Hidden size | 1 280 |
| Layers | 28 |
| Vocab size | 64 000 (custom KK/RU tokenizer) |
| Precision | BF16 |
| Disk footprint | ~1.3 GB |
| Merge method | DARE-TIES (RNG seed 1729) |
| Primary language | Kazakh (KK) |
| Secondary language | Russian (RU) |
---
## Source models
| Model | Role | Weight | Density |
| --- | --- | --- | --- |
| `ekitil-core-qwen3-600m-kkru-base-v1` | Base (foundation) | -- | -- |
| `ekitil-qwen3-600m-kk` (step 4500) | KK specialist | 0.45 | 0.53 |
| `ekitil-qwen3-600m-kkru` (step 2000) | KK+RU generalist | 0.35 | 0.53 |
The base model provides the foundation architecture. DARE randomly drops (1 - density) of each
task vector's weights and rescales survivors, then TIES elects majority-sign directions before
summing into the merged model.
---
## Why this merge
Each source model captures a different aspect of Kazakh language:
- **ekitil-core** -- balanced KK+RU base
- **ekitil-kk** -- maximally Kazakh-specialized (4 500 training steps)
- **ekitil-kkru** -- bilingual KK+RU (2 000 training steps)
DARE-TIES combines all three while suppressing conflicting parameter updates, producing better
KK coverage than any single model alone.
---
## How to use
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
model_id = "AMAImedia/NOESIS-Qwen3-0.6B-Darwin-Ekitil-Sozkz-KZ-BF16"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype=torch.bfloat16,
device_map="auto",
)
messages = [{"role": "user", "content": "Salem! Qazaq tilinde soylesesik."}]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(text, return_tensors="pt").to(model.device)
out = model.generate(**inputs, max_new_tokens=256, do_sample=True, temperature=0.7)
print(tokenizer.decode(out[0][inputs.input_ids.shape[1]:], skip_special_tokens=True))
```
> **Note:** `vocab_size=64000` -- custom Kazakh tokenizer, not Qwen3 standard 151 936.
> Not compatible with standard Qwen3 tokenizer pipelines.
---
## NOESIS context
In NOESIS this model provides **Kazakh language domain boost** (KK x10 weight multiplier)
for the DUB-LM and CHAT specialists during knowledge distillation.
> **KD note:** `vocab_size=64000` is incompatible with NOESIS student vocab (151 936).
> Soft label extraction requires a custom cross-vocab projection layer.
---
## Provenance
A `merge_provenance.json` file ships alongside the model weights with the full merge trace:
source models, weights, densities, DARE-TIES parameters, and RNG seed.
---
## License
This model is released under the **Apache License 2.0**, inherited from the upstream Qwen3
base and ekitil model checkpoints. See the `LICENSE` file for the full license text.
---
## Citation
```bibtex
@misc{noesis_darwin_kz,
title = {NOESIS-Qwen3-0.6B-Darwin-Ekitil-Sozkz-KZ-BF16},
author = {Bolotnikov, Ilia},
year = {2026},
publisher = {AMAImedia},
url = {https://amaimedia.com}
}
```

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{
"architectures": [
"Qwen3ForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": null,
"dtype": "float32",
"eos_token_id": null,
"head_dim": 64,
"hidden_act": "silu",
"hidden_size": 1280,
"initializer_range": 0.02,
"intermediate_size": 4480,
"layer_types": [
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
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"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention"
],
"max_position_embeddings": 2048,
"max_window_layers": 28,
"model_type": "qwen3",
"num_attention_heads": 20,
"num_hidden_layers": 28,
"num_key_value_heads": 4,
"pad_token_id": null,
"rms_norm_eps": 1e-06,
"rope_parameters": {
"rope_theta": 1000000,
"rope_type": "default"
},
"sliding_window": null,
"tie_word_embeddings": true,
"transformers_version": "5.5.0",
"use_cache": true,
"use_sliding_window": false,
"vocab_size": 64000,
"_name_or_path": "amaimedia/NOESIS-Qwen3-0.6B-Darwin-Ekitil-Sozkz-KZ-BF16"
}

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{
"_from_model_config": true,
"output_attentions": false,
"output_hidden_states": false,
"transformers_version": "5.5.0",
"use_cache": true
}

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{
"noesis_version": "v14.7",
"method": "DARE-TIES",
"seed": 1729,
"base": "B:\\Downloads\\Portable\\NOESIS-VC-ONE\\models\\llm\\sozkz\\ekitil-core-qwen3-600m-kkru-base-v1",
"models": [
{
"path": "B:\\Downloads\\Portable\\NOESIS-VC-ONE\\models\\llm\\sozkz\\ekitil-qwen3-600m-kk\\step_4500",
"weight": 0.45,
"density": 0.53
},
{
"path": "B:\\Downloads\\Portable\\NOESIS-VC-ONE\\models\\llm\\sozkz\\ekitil-qwen3-600m-kkru\\step_2000",
"weight": 0.35,
"density": 0.53
}
],
"output": "B:\\Downloads\\Portable\\NOESIS-VC-ONE\\models\\llm\\NOESIS-Qwen3-0.6B-Darwin-Ekitil-Sozkz-KZ-BF16"
}

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