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Model: SantiagoC/palindrome-curriculum-v2 Source: Original Platform
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README.md
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---
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base_model: SantiagoC/palindrome-sft-qwen3
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library_name: transformers
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model_name: palindrome-curriculum-v2
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tags:
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- generated_from_trainer
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- grpo
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- trackio:https://huggingface.co/spaces/SantiagoC/palindrome-curriculum-static-3736fc
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- hf_jobs
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- trackio
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- trl
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- ml-intern
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licence: license
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---
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# Model Card for palindrome-curriculum-v2
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This model is a fine-tuned version of [SantiagoC/palindrome-sft-qwen3](https://huggingface.co/SantiagoC/palindrome-sft-qwen3).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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```python
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from transformers import pipeline
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question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
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generator = pipeline("text-generation", model="SantiagoC/palindrome-curriculum-v2", device="cuda")
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output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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print(output["generated_text"])
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```
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## Training procedure
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This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).
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### Framework versions
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- TRL: 1.3.0
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- Transformers: 5.8.0
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- Pytorch: 2.11.0
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- Datasets: 4.8.5
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- Tokenizers: 0.22.2
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## Citations
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Cite GRPO as:
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```bibtex
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@article{shao2024deepseekmath,
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title = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},
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author = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo},
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year = 2024,
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eprint = {arXiv:2402.03300},
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}
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```
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Cite TRL as:
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```bibtex
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@software{vonwerra2020trl,
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title = {{TRL: Transformers Reinforcement Learning}},
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author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
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license = {Apache-2.0},
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url = {https://github.com/huggingface/trl},
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year = {2020}
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}
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```
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<!-- ml-intern-provenance -->
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## Generated by ML Intern
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This model repository was generated by [ML Intern](https://github.com/huggingface/ml-intern), an agent for machine learning research and development on the Hugging Face Hub.
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- Try ML Intern: https://smolagents-ml-intern.hf.space
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- Source code: https://github.com/huggingface/ml-intern
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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 = 'SantiagoC/palindrome-curriculum-v2'
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(model_id)
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```
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For non-causal architectures, replace `AutoModelForCausalLM` with the appropriate `AutoModel` class.
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89
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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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": 40960,
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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": "5.8.0",
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"use_cache": false,
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"use_sliding_window": false,
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"vocab_size": 151936
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}
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generation_config.json
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{
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"do_sample": true,
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"eos_token_id": [
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151645,
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151643
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],
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"pad_token_id": 151643,
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"temperature": 0.6,
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"top_k": 20,
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"top_p": 0.95,
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"transformers_version": "5.8.0"
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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:f36458e515e8721fb652e24466cfea9cc30db8f19ea956a8e12777bc85551f92
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size 2384234968
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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:be75606093db2094d7cd20f3c2f385c212750648bd6ea4fb2bf507a6a4c55506
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size 11422650
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32
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": false,
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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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"padding_side": "left",
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"split_special_tokens": false,
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"tokenizer_class": "Qwen2Tokenizer",
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"truncation_side": "left",
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"unk_token": null
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}
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3
training_args.bin
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:845605815cd98b9ce6427211ebffc71fa11c348e4d278912cf86e26bb0037f83
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size 7313
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