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Model: Lixiaojian123/qwen3-0.6b-sft Source: Original Platform
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README.md
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README.md
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---
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language:
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- zh
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- en
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license: apache-2.0
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base_model: Qwen/Qwen3-0.6B-Base
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- qwen3
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- qwen3-0.6b
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- sft
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- trl
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- smoltalk2
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- instruction-tuned
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datasets:
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- HuggingFaceTB/smoltalk2
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---
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# Qwen3-0.6B SFT on SmolTalk2
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This model is a supervised fine-tuned version of `Qwen/Qwen3-0.6B-Base`.
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It was trained with TRL SFT on selected no-think splits from `HuggingFaceTB/smoltalk2`.
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The chat template was copied from the Qwen3 Instruct tokenizer so the model can be used with the standard chat-message interface.
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## Training
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- Base model: `Qwen/Qwen3-0.6B-Base`
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- Method: full-parameter SFT
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- Framework: TRL / Transformers
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- Dataset: `HuggingFaceTB/smoltalk2`, config `SFT`
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- Splits:
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- `smoltalk_smollm3_smol_magpie_ultra_no_think`
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- `OpenHermes_2.5_no_think`
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- `tulu_3_sft_personas_instruction_following_no_think`
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- `smoltalk_smollm3_systemchats_30k_no_think`
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- Max length: 2048
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- Steps: 5000
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- Learning rate: 2e-5, cosine schedule, warmup ratio 0.03
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- Effective batch size: 64
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- Gradient clipping: 1.0
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## Evaluation
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The table below compares the official Qwen3-0.6B Instruct model against the official Base model using `lm-eval`.
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| Task | Base | Instruct | Delta |
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| ---- | ---: | -------: | ----: |
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| `ifeval` | 16.27% | 43.62% | +27.36pp |
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| `truthfulqa_mc2` | 45.98% | 42.84% | -3.15pp |
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| `mmlu` | 50.46% | 40.26% | -10.20pp |
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| `arc_challenge` | 38.65% | 34.13% | -4.52pp |
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| `hellaswag` | 53.67% | 47.29% | -6.38pp |
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| `winogrande` | 58.56% | 56.35% | -2.21pp |
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| `gsm8k_cot` | 55.50% | 4.55% | -50.95pp |
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The locally trained SFT checkpoint used as the DPO reference scored as follows:
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| Task | SFT score |
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| ---- | --------: |
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| `ifeval` | 39.19% |
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| `truthfulqa_mc2` | 46.52% |
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| `mmlu` | 49.35% |
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| `arc_challenge` | 37.03% |
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| `hellaswag` | 53.36% |
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| `winogrande` | 57.93% |
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| `gsm8k_cot` | 48.37% |
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## Usage
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_id = "Lixiaojian123/qwen3-0.6b-sft"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")
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messages = [
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{"role": "user", "content": "用三句话解释什么是监督微调。"},
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]
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inputs = tokenizer.apply_chat_template(
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messages,
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tokenize=True,
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add_generation_prompt=True,
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return_tensors="pt",
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).to(model.device)
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outputs = model.generate(inputs, max_new_tokens=256)
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print(tokenizer.decode(outputs[0][inputs.shape[-1]:], skip_special_tokens=True))
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```
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## Limitations
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This is a small 0.6B parameter model. It may hallucinate, make reasoning mistakes, and fail on complex instructions. The model was trained primarily on no-think instruction data, so it is not intended to expose long chain-of-thought traces.
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chat_template.jinja
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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 message in messages[::-1] %}
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{%- set index = (messages|length - 1) - loop.index0 %}
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{%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
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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.content is string %}
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{%- set content = message.content %}
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{%- else %}
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{%- set content = '' %}
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{%- endif %}
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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' + content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{%- set reasoning_content = '' %}
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{%- if message.reasoning_content is string %}
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{%- set reasoning_content = message.reasoning_content %}
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{%- else %}
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{%- if '</think>' in content %}
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{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
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{%- set content = content.split('</think>')[-1].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 %}
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{%- 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' }}
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{%- endif %}
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{%- if tool_call.function %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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{{- '<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
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{{- '", "arguments": ' }}
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{%- if tool_call.arguments is string %}
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{{- tool_call.arguments }}
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{%- else %}
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{{- tool_call.arguments | tojson }}
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{%- endif %}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{%- endif %}
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{{- '<|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 %}
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{{- '\n<tool_response>\n' }}
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{{- content }}
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{{- '\n</tool_response>' }}
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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{{- '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- 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 %}
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{{- '<think>\n\n</think>\n\n' }}
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{%- endif %}
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{%- endif %}
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63
config.json
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config.json
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{
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"architectures": [
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"Qwen3ForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": null,
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"dtype": "float32",
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"eos_token_id": 151645,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 1024,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_types": [
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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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"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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"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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"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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"full_attention"
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],
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"max_position_embeddings": 32768,
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"max_window_layers": 28,
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"model_type": "qwen3",
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"num_attention_heads": 16,
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"num_hidden_layers": 28,
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"num_key_value_heads": 8,
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"pad_token_id": 151643,
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"rms_norm_eps": 1e-06,
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"rope_parameters": {
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"rope_theta": 1000000,
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"rope_type": "default"
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},
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"sliding_window": null,
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"tie_word_embeddings": true,
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"transformers_version": "5.12.1",
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"use_cache": false,
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"use_sliding_window": false,
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"vocab_size": 151680
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}
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generation_config.json
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generation_config.json
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{
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"do_sample": false,
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"eos_token_id": [
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151645
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],
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"max_new_tokens": 2048,
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"pad_token_id": 151643,
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"transformers_version": "5.12.1"
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}
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model.safetensors
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:adb001958b26f862841a460c3ee700b3c446a8d4ad6a31c77a73e3d72e387365
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size 2383186392
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3
tokenizer.json
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:950f6da859bb15a1033a243c55a7f70e555072f068f05368baab9d6b03b4c8d1
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size 11424730
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tokenizer_config.json
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{
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"add_prefix_space": false,
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"backend": "tokenizers",
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"bos_token": null,
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"clean_up_tokenization_spaces": false,
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"eos_token": "<|im_end|>",
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"errors": "replace",
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"extra_special_tokens": [
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"<|im_start|>",
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"<|im_end|>",
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"<|object_ref_start|>",
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"<|object_ref_end|>",
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"<|box_start|>",
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"<|box_end|>",
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"<|quad_start|>",
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"<|quad_end|>",
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"<|vision_start|>",
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"<|vision_end|>",
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"<|vision_pad|>",
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"<|image_pad|>",
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"<|video_pad|>"
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],
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"is_local": true,
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"local_files_only": false,
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"model_max_length": 131072,
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"pad_token": "<|endoftext|>",
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"split_special_tokens": false,
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"tokenizer_class": "Qwen2Tokenizer",
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"unk_token": null
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}
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