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Model: inspirebek/qwen3-4b-uzbek-v2 Source: Original Platform
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134
README.md
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---
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language:
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- uz
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- en
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license: cc-by-nc-4.0
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datasets:
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- yakhyo/uz-wiki
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- tahrirchi/uz-books-v2
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- tahrirchi/uz-crawl
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- saillab/alpaca_uzbek_taco
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- behbudiy/alpaca-cleaned-uz
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- UAzimov/uzbek-instruct-llm
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- CohereLabs/aya_collection_language_split
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- med-alex/qa_mt_ru_to_uzn
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- med-alex/qa_mt_tr_to_uzn
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library_name: transformers
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pipeline_tag: text-generation
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base_model: Qwen/Qwen3-4B
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tags:
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- uzbek
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- qwen3
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- lora
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- merged
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- sft
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- continued-pretraining
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---
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# qwen3-4b-uzbek-v2
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merged bf16 uzbek fine-tune of `Qwen/Qwen3-4B`. standalone — loadable without peft.
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## usage
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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tok = AutoTokenizer.from_pretrained("inspirebek/qwen3-4b-uzbek-v2")
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model = AutoModelForCausalLM.from_pretrained(
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"inspirebek/qwen3-4b-uzbek-v2",
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dtype=torch.bfloat16,
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device_map="auto",
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)
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messages = [{"role": "user", "content": "O‘zbekiston poytaxti qayer?"}]
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inputs = tok.apply_chat_template(messages, return_tensors="pt", add_generation_prompt=True).to(model.device)
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out = model.generate(inputs, max_new_tokens=256, do_sample=True, temperature=0.7)
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print(tok.decode(out[0][inputs.shape[1]:], skip_special_tokens=True))
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```
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## training
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a two-stage lora fine-tune of `Qwen/Qwen3-4B`. the hard parts weren't the training loop — they were figuring out why v1 failed, then engineering around a 16-hour compute timeout that couldn't fit the full run.
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### the v1 lesson: why plain lora collapsed to random
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v1 scored **26.92%** on mmlu-uz, statistically indistinguishable from 25% random baseline. the adapter was training and loss was descending, but the model learned nothing useful in uzbek. root cause: lora only touched the attention and mlp projections. for a base model with english-dominant pretraining, learning a new language requires **re-mapping the vocabulary itself** — which lives in `embed_tokens` (input embeddings) and `lm_head` (output projection). freezing both means the model can't reshape its token distribution over uzbek morphology, only nudge how it attends within the english-shaped geometry it already has.
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v2 adds `embed_tokens` and `lm_head` to `target_modules`. this expands the lora to ~2 gb (vs ~200 mb in v1) but finally lets the model actually learn uzbek. result: **mmlu-uz jumped to 40.50%** (+13.58 pp over random).
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### recipe
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**lora configuration** (`unsloth` + `peft`):
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- `r=64`, `alpha=128` — alpha = 2·r (more aggressive updates than the conservative alpha=r default)
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- `use_rslora=True` — alpha scales by `alpha/sqrt(r)` instead of `alpha/r`; without this the per-parameter update magnitude at r=64 is too small and training stagnates
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- target modules: `q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj, embed_tokens, lm_head`
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- `use_gradient_checkpointing="unsloth"` to fit the expanded adapter on a single l4
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**dual learning rate** (via `UnslothTrainer`):
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- base lr for projection layers, `embedding_learning_rate` at 1/10th for `embed_tokens` + `lm_head`
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- embeddings are the highest-leverage layer — a full-lr update can catastrophically drift the model's token geometry in the first few hundred steps
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**stage a — continued pretraining** on native uzbek text (3 datasets, ~2m rows):
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- `lr=5e-5`, `embedding_lr=5e-6`, 1 epoch, `packing=False`
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- the goal is to reshape the token distribution so the model fluently predicts uzbek sequences, not to learn task behavior
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**stage b — supervised fine-tune** on chat-formatted uzbek instructions (6 datasets, ~4.3m rows):
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- loaded from the stage a adapter (continues training, not a fresh start)
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- `lr=1e-4`, `embedding_lr=1e-5`, 1 epoch
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- `train_on_responses_only=True`: the loss is masked on the user side of the qwen3 chat template so gradient only flows through assistant responses; prevents the model from memorizing prompt patterns and gives +1–2% accuracy empirically
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**stable batching**:
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- `per_device_train_batch_size=1`, `gradient_accumulation_steps=16` — effective batch 16
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- at r=64 with embedding lora, batch 2 oom's on 24gb. the accumulation trick keeps gradient signal while staying inside the vram budget
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**optimization**: `adamw_8bit` (bitsandbytes) + cosine schedule + 3% warmup, weight decay 0.01, seed 3407.
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### infra: surviving a 16-hour timeout on serverless gpu
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modal functions have a 16-hour hard cap. stage b doesn't fit in 16 hours on a single l4, and a mid-epoch restart on a fresh container would lose everything (the `/ckpts/` volume persists, but the container that owns the training state doesn't).
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the fix: a `TrainerCallback` that pushes each checkpoint to a private hugging face repo (`inspirebek/qwen3-4b-uzbek-ckpts`) on every `save_steps` fire. when the container timed out at step 7258 / 8242 (88%), the next run loaded `checkpoint-7000` from the hf backup and resumed — on a different modal account, after the first account's $30 credit ran out. account switches are invisible to huggingface; the backup was the portable state.
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total stage b runtime: ~10 h first leg + ~3.2 h resume leg = ~13.2 h on a single l4.
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### evaluation
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- **mmlu-uz** (murodbek/MMLU-uz, zero-shot, logit-based multiple choice): **40.50%** overall
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- social sciences 45.43%, other 45.07%, business 42.42%, stem 41.67%, medical 39.67%, humanities 35.60%
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- **uzlib** (tahrirchi/uzlib, uzbek linguistic benchmark, sampled generation t=1.0 p=0.95): **33.42%** overall
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- correct_word 34.98%, fill_in 30.77%, meaning 26.69%, meaning_in_context 25.00%
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- 8.17% of responses didn't parse cleanly as `A/B/C/D` — a fraction of the score loss is format drift, not knowledge
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## datasets
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**stage a — fluency (continued pretraining):**
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- [`yakhyo/uz-wiki`](https://huggingface.co/datasets/yakhyo/uz-wiki) · MIT
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- [`tahrirchi/uz-books-v2`](https://huggingface.co/datasets/tahrirchi/uz-books-v2) · MIT
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- [`tahrirchi/uz-crawl`](https://huggingface.co/datasets/tahrirchi/uz-crawl) · Apache-2.0
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**stage b — instruct (sft):**
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|
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- [`saillab/alpaca_uzbek_taco`](https://huggingface.co/datasets/saillab/alpaca_uzbek_taco) · CC-BY-NC-4.0
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- [`behbudiy/alpaca-cleaned-uz`](https://huggingface.co/datasets/behbudiy/alpaca-cleaned-uz) · CC-BY-4.0
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- [`UAzimov/uzbek-instruct-llm`](https://huggingface.co/datasets/UAzimov/uzbek-instruct-llm) · Apache-2.0
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- [`CohereLabs/aya_collection_language_split`](https://huggingface.co/datasets/CohereLabs/aya_collection_language_split) · Apache-2.0
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||||
- [`med-alex/qa_mt_ru_to_uzn`](https://huggingface.co/datasets/med-alex/qa_mt_ru_to_uzn) · unspecified
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- [`med-alex/qa_mt_tr_to_uzn`](https://huggingface.co/datasets/med-alex/qa_mt_tr_to_uzn) · unspecified
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> ⚠️ 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.
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## sibling formats
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- [`inspirebek/qwen3-4b-uzbek-v2`](https://huggingface.co/inspirebek/qwen3-4b-uzbek-v2)
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- [`inspirebek/qwen3-4b-uzbek-v2-lora`](https://huggingface.co/inspirebek/qwen3-4b-uzbek-v2-lora)
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- [`inspirebek/qwen3-4b-uzbek-v2-bnb-4bit`](https://huggingface.co/inspirebek/qwen3-4b-uzbek-v2-bnb-4bit)
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- [`inspirebek/qwen3-4b-uzbek-v2-awq`](https://huggingface.co/inspirebek/qwen3-4b-uzbek-v2-awq)
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- [`inspirebek/qwen3-4b-uzbek-v2-GGUF`](https://huggingface.co/inspirebek/qwen3-4b-uzbek-v2-GGUF)
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## intended use & limitations
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uzbek-first chat assistant. capable in english as well. not aligned for safety — treat as a research artifact. knowledge cutoff inherits from `Qwen/Qwen3-4B`.
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28
added_tokens.json
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{
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"</think>": 151668,
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"</tool_call>": 151658,
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"</tool_response>": 151666,
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"<think>": 151667,
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"<tool_call>": 151657,
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"<tool_response>": 151665,
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"<|box_end|>": 151649,
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"<|box_start|>": 151648,
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"<|endoftext|>": 151643,
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"<|file_sep|>": 151664,
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"<|fim_middle|>": 151660,
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"<|fim_pad|>": 151662,
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"<|fim_prefix|>": 151659,
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"<|fim_suffix|>": 151661,
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"<|im_end|>": 151645,
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"<|im_start|>": 151644,
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"<|image_pad|>": 151655,
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"<|object_ref_end|>": 151647,
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"<|object_ref_start|>": 151646,
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"<|quad_end|>": 151651,
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"<|quad_start|>": 151650,
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"<|repo_name|>": 151663,
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"<|video_pad|>": 151656,
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"<|vision_end|>": 151653,
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"<|vision_pad|>": 151654,
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"<|vision_start|>": 151652
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}
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chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0].role == 'system' %}
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{{- messages[0].content + '\n\n' }}
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{%- endif %}
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{{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
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{%- else %}
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{%- if messages[0].role == 'system' %}
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{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
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{%- for forward_message in messages %}
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{%- set index = (messages|length - 1) - loop.index0 %}
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{%- set message = messages[index] %}
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{%- set current_content = message.content if message.content is not none else '' %}
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{%- set tool_start = '<tool_response>' %}
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{%- set tool_start_length = tool_start|length %}
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{%- set start_of_message = current_content[:tool_start_length] %}
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{%- set tool_end = '</tool_response>' %}
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{%- set tool_end_length = tool_end|length %}
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{%- set start_pos = (current_content|length) - tool_end_length %}
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{%- if start_pos < 0 %}
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{%- set start_pos = 0 %}
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{%- endif %}
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{%- set end_of_message = current_content[start_pos:] %}
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{%- if ns.multi_step_tool and message.role == "user" and not(start_of_message == tool_start and end_of_message == tool_end) %}
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{%- set ns.multi_step_tool = false %}
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{%- set ns.last_query_index = index %}
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{%- endif %}
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{%- endfor %}
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{%- for message in messages %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
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{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{%- set content = message.content %}
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{%- set reasoning_content = '' %}
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{%- if message.reasoning_content is defined and message.reasoning_content is not none %}
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{%- set reasoning_content = message.reasoning_content %}
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{%- else %}
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{%- if '</think>' in message.content %}
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{%- set content = (message.content.split('</think>')|last).lstrip('\n') %}
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{%- set reasoning_content = (message.content.split('</think>')|first).rstrip('\n') %}
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{%- set reasoning_content = (reasoning_content.split('<think>')|last).lstrip('\n') %}
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{%- endif %}
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{%- endif %}
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{%- if loop.index0 > ns.last_query_index %}
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{%- if loop.last or (not loop.last and reasoning_content) %}
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{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
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{%- else %}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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{%- endif %}
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{%- else %}
|
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{{- '<|im_start|>' + message.role + '\n' + content }}
|
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{%- endif %}
|
||||
{%- if message.tool_calls %}
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{%- for tool_call in message.tool_calls %}
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{%- if (loop.first and content) or (not loop.first) %}
|
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{{- '\n' }}
|
||||
{%- endif %}
|
||||
{%- if tool_call.function %}
|
||||
{%- set tool_call = tool_call.function %}
|
||||
{%- endif %}
|
||||
{{- '<tool_call>\n{"name": "' }}
|
||||
{{- tool_call.name }}
|
||||
{{- '", "arguments": ' }}
|
||||
{%- if tool_call.arguments is string %}
|
||||
{{- tool_call.arguments }}
|
||||
{%- else %}
|
||||
{{- tool_call.arguments | tojson }}
|
||||
{%- endif %}
|
||||
{{- '}\n</tool_call>' }}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
{{- '<|im_end|>\n' }}
|
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{%- elif message.role == "tool" %}
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{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
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{{- '<|im_start|>user' }}
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||||
{%- endif %}
|
||||
{{- '\n<tool_response>\n' }}
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||||
{{- message.content }}
|
||||
{{- '\n</tool_response>' }}
|
||||
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
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||||
{%- if add_generation_prompt %}
|
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{{- '<|im_start|>assistant\n' }}
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||||
{%- if enable_thinking is defined and enable_thinking is false %}
|
||||
{{- '<think>\n\n</think>\n\n' }}
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||||
{%- endif %}
|
||||
{%- endif %}
|
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68
config.json
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config.json
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{
|
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"architectures": [
|
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"Qwen3ForCausalLM"
|
||||
],
|
||||
"attention_bias": false,
|
||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": 151643,
|
||||
"dtype": "bfloat16",
|
||||
"eos_token_id": 151645,
|
||||
"head_dim": 128,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 2560,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 9728,
|
||||
"layer_types": [
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
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"full_attention",
|
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"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
||||
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"model.layers.7.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.norm.weight": "model-00002-of-00002.safetensors"
|
||||
}
|
||||
}
|
||||
31
special_tokens_map.json
Normal file
31
special_tokens_map.json
Normal file
@@ -0,0 +1,31 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"eos_token": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|vision_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
Binary file not shown.
240
tokenizer_config.json
Normal file
240
tokenizer_config.json
Normal file
@@ -0,0 +1,240 @@
|
||||
{
|
||||
"add_bos_token": false,
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"151643": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151644": {
|
||||
"content": "<|im_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151645": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151646": {
|
||||
"content": "<|object_ref_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151647": {
|
||||
"content": "<|object_ref_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151648": {
|
||||
"content": "<|box_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151649": {
|
||||
"content": "<|box_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151650": {
|
||||
"content": "<|quad_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151651": {
|
||||
"content": "<|quad_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151652": {
|
||||
"content": "<|vision_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151653": {
|
||||
"content": "<|vision_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151654": {
|
||||
"content": "<|vision_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151655": {
|
||||
"content": "<|image_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151656": {
|
||||
"content": "<|video_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151657": {
|
||||
"content": "<tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151658": {
|
||||
"content": "</tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151659": {
|
||||
"content": "<|fim_prefix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151660": {
|
||||
"content": "<|fim_middle|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151661": {
|
||||
"content": "<|fim_suffix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151662": {
|
||||
"content": "<|fim_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151665": {
|
||||
"content": "<tool_response>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151666": {
|
||||
"content": "</tool_response>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151667": {
|
||||
"content": "<think>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151668": {
|
||||
"content": "</think>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 40960,
|
||||
"pad_token": "<|vision_pad|>",
|
||||
"padding_side": "left",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user