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Model: STEVENZHANG904/Qwen3-0.6B-planner-sft Source: Original Platform
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README.md
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README.md
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---
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license: apache-2.0
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base_model: Qwen/Qwen3-0.6B
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datasets:
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- Divij/qwen3-32b-mas-traces
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language:
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- en
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library_name: transformers
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tags:
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- sft
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- qwen3
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- multi-agent
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- distillation
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- planner
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---
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# STEVENZHANG904/Qwen3-0.6B-planner-sft
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SFT-finetuned **Qwen/Qwen3-0.6B** on the **planner** subset of [Divij/qwen3-32b-mas-traces](https://huggingface.co/datasets/Divij/qwen3-32b-mas-traces),
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which contains traces of **Qwen3-32B** acting as a `planner` agent in a multi-agent system. This model is the
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distilled student that learns to play the same role as Qwen3-32B in that pipeline.
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## Branches
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| Branch | Epochs trained | Notes |
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|---|---|---|
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| `epoch2` | 2 | intermediate |
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| `epoch5` | 5 | intermediate |
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| `main` | 10 | final |
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## Training configuration
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- **Base model:** `Qwen/Qwen3-0.6B`
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- **Dataset:** `Divij/qwen3-32b-mas-traces` (config `planner`)
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- **Loss:** assistant-only (system + user tokens masked)
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- **Optimizer:** AdamW (β=(0.9, 0.95), wd=0.01, eps=1e-8)
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- **Learning rate:** 1e-5, constant with 3% warmup
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- **Sequence length:** 8192 (sequence packing on)
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- **Precision:** bf16
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- **Hardware:** 8× H100 80GB, DDP
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- **Liger-Kernel:** on (chunked CE + fused RMSNorm)
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## Inference
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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repo = "STEVENZHANG904/Qwen3-0.6B-planner-sft"
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tok = AutoTokenizer.from_pretrained(repo)
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model = AutoModelForCausalLM.from_pretrained(repo, dtype=torch.bfloat16, device_map="cuda")
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# Planner role expects a task-spec prompt — see the dataset card for the exact format.
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messages = [
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{"role": "system", "content": "You are a helpful, creative, and smart assistant."},
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{"role": "user", "content": "<your planner task spec here>"},
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]
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inputs = tok.apply_chat_template(messages, return_tensors="pt", add_generation_prompt=True).to("cuda")
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out = model.generate(
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inputs, max_new_tokens=4096,
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do_sample=True, temperature=0.6, top_p=0.95, # Qwen3 thinking-mode defaults
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)
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print(tok.decode(out[0][inputs.shape[-1]:], skip_special_tokens=True))
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```
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The model emits `<think>...</think>` reasoning blocks (inherited from Qwen3-32B traces).
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**Use sampling**, not greedy decoding — small distilled models can loop in `<think>` under greedy.
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config.json
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config.json
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{
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"Qwen3ForCausalLM"
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],
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|
||||
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role == 'system' %}\n {{- messages[0].content + '\\n\\n' }}\n {%- endif %}\n {{- \"# 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>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\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\" }}\n{%- else %}\n {%- if messages[0].role == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n {%- set index = (messages|length - 1) - loop.index0 %}\n {%- 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>')) %}\n {%- set ns.multi_step_tool = false %}\n {%- set ns.last_query_index = index %}\n {%- endif %}\n{%- endfor %}\n{%- for message in messages %}\n {%- if message.content is string %}\n {%- set content = message.content %}\n {%- else %}\n {%- set content = '' %}\n {%- endif %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {%- set reasoning_content = '' %}\n {%- if message.reasoning_content is string %}\n {%- set reasoning_content = message.reasoning_content %}\n {%- else %}\n {%- if '</think>' in content %}\n {%- set reasoning_content = content.split('</think>')[0].rstrip('\\n').split('<think>')[-1].lstrip('\\n') %}\n {%- set content = content.split('</think>')[-1].lstrip('\\n') %}\n {%- endif %}\n {%- endif %}\n {%- if loop.index0 > ns.last_query_index %}\n {%- if loop.last or (not loop.last and reasoning_content) %}\n {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content.strip('\\n') + '\\n</think>\\n\\n' + content.lstrip('\\n') }}\n {%- else %}\n {{- '<|im_start|>' + message.role + '\\n' + content }}\n {%- endif %}\n {%- else %}\n {{- '<|im_start|>' + message.role + '\\n' + content }}\n {%- endif %}\n {%- if message.tool_calls %}\n {%- for tool_call in message.tool_calls %}\n {%- if (loop.first and content) or (not loop.first) %}\n {{- '\\n' }}\n {%- endif %}\n {%- if tool_call.function %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {%- if tool_call.arguments is string %}\n {{- tool_call.arguments }}\n {%- else %}\n {{- tool_call.arguments | tojson }}\n {%- endif %}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {%- endif %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n {%- if enable_thinking is defined and enable_thinking is false %}\n {{- '<think>\\n\\n</think>\\n\\n' }}\n {%- endif %}\n{%- endif %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"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