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Model: inspirebek/qwen3-4b-uzbek-v2-awq
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---
language:
- uz
- en
license: cc-by-nc-4.0
datasets:
- yakhyo/uz-wiki
- tahrirchi/uz-books-v2
- tahrirchi/uz-crawl
- saillab/alpaca_uzbek_taco
- behbudiy/alpaca-cleaned-uz
- UAzimov/uzbek-instruct-llm
- CohereLabs/aya_collection_language_split
- med-alex/qa_mt_ru_to_uzn
- med-alex/qa_mt_tr_to_uzn
library_name: transformers
pipeline_tag: text-generation
base_model: inspirebek/qwen3-4b-uzbek-v2
tags:
- uzbek
- qwen3
- quantized
- 4-bit
- awq
---
# qwen3-4b-uzbek-v2-awq
awq 4-bit activation-aware quant (~3.4 gb) of [`inspirebek/qwen3-4b-uzbek-v2`](https://huggingface.co/inspirebek/qwen3-4b-uzbek-v2). fast gpu inference via vllm / tgi / transformers.
## usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
tok = AutoTokenizer.from_pretrained("inspirebek/qwen3-4b-uzbek-v2-awq")
model = AutoModelForCausalLM.from_pretrained(
"inspirebek/qwen3-4b-uzbek-v2-awq",
device_map="auto",
)
```
with vllm:
```bash
vllm serve inspirebek/qwen3-4b-uzbek-v2-awq --quantization awq --dtype float16
```
## quantization
- method: awq (`autoawq` 0.2.9, gemm version)
- `w_bit=4, q_group_size=128, zero_point=True`
- calibration: 128 uzbek samples (2048 tokens each) from `fluency.jsonl`
## datasets
**stage a — fluency (continued pretraining):**
- [`yakhyo/uz-wiki`](https://huggingface.co/datasets/yakhyo/uz-wiki) · MIT
- [`tahrirchi/uz-books-v2`](https://huggingface.co/datasets/tahrirchi/uz-books-v2) · MIT
- [`tahrirchi/uz-crawl`](https://huggingface.co/datasets/tahrirchi/uz-crawl) · Apache-2.0
**stage b — instruct (sft):**
- [`saillab/alpaca_uzbek_taco`](https://huggingface.co/datasets/saillab/alpaca_uzbek_taco) · CC-BY-NC-4.0
- [`behbudiy/alpaca-cleaned-uz`](https://huggingface.co/datasets/behbudiy/alpaca-cleaned-uz) · CC-BY-4.0
- [`UAzimov/uzbek-instruct-llm`](https://huggingface.co/datasets/UAzimov/uzbek-instruct-llm) · Apache-2.0
- [`CohereLabs/aya_collection_language_split`](https://huggingface.co/datasets/CohereLabs/aya_collection_language_split) · Apache-2.0
- [`med-alex/qa_mt_ru_to_uzn`](https://huggingface.co/datasets/med-alex/qa_mt_ru_to_uzn) · unspecified
- [`med-alex/qa_mt_tr_to_uzn`](https://huggingface.co/datasets/med-alex/qa_mt_tr_to_uzn) · unspecified
> ⚠️ licensing note: `saillab/alpaca_uzbek_taco` is cc-by-nc-4.0, which restricts commercial use of derivative models. downstream users who need a fully permissive license should retrain without that subset.
## sibling formats
- [`inspirebek/qwen3-4b-uzbek-v2`](https://huggingface.co/inspirebek/qwen3-4b-uzbek-v2)
- [`inspirebek/qwen3-4b-uzbek-v2-lora`](https://huggingface.co/inspirebek/qwen3-4b-uzbek-v2-lora)
- [`inspirebek/qwen3-4b-uzbek-v2-bnb-4bit`](https://huggingface.co/inspirebek/qwen3-4b-uzbek-v2-bnb-4bit)
- [`inspirebek/qwen3-4b-uzbek-v2-awq`](https://huggingface.co/inspirebek/qwen3-4b-uzbek-v2-awq)
- [`inspirebek/qwen3-4b-uzbek-v2-GGUF`](https://huggingface.co/inspirebek/qwen3-4b-uzbek-v2-GGUF)

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