sdft-modelv2
Browse files- .gitattributes +1 -0
- README.md +68 -0
- chat_template.jinja +54 -0
- config.json +61 -0
- generation_config.json +13 -0
- model.safetensors +3 -0
- tokenizer.json +3 -0
- tokenizer_config.json +32 -0
- training_args.bin +3 -0
.gitattributes
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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base_model: Qwen/Qwen2.5-1.5B-Instruct
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library_name: transformers
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model_name: sdft-modelv2
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tags:
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- generated_from_trainer
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- sdft
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- trl
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- hf_jobs
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licence: license
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---
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# Model Card for sdft-modelv2
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This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct).
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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="moos124/sdft-modelv2", 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 SDFT, a method introduced in [Self-Training with On-Policy Self-Distillation for Language Model Alignment](https://huggingface.co/papers/2601.19897).
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### Framework versions
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- TRL: 1.3.0
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- Transformers: 5.7.0
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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 SDFT as:
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```bibtex
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@article{hubotter2026selftraining,
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title = {{Self-Training with On-Policy Self-Distillation for Language Model Alignment}},
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author = {Jonas H\"ubotter and Frederike L\"ubeck and Lejs Behric and Anton Baumann and Marco Bagatella and Daniel Marta and Ido Hakimi and Idan Shenfeld and Thomas Kleine Buening and Carlos Guestrin and Andreas Krause},
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year = 2026,
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eprint = {arXiv:2601.19897}
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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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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'] }}
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{%- else %}
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{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
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{%- endif %}
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{{- "\n\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>" }}
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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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{%- else %}
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{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- for message in messages %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
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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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{{- '<|im_start|>' + message.role }}
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{%- if message.content %}
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{{- '\n' + message.content }}
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{%- endif %}
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{%- for tool_call in message.tool_calls %}
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{%- if tool_call.function is defined %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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{{- '\n<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
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{{- '", "arguments": ' }}
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{{- tool_call.arguments | tojson }}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{{- '<|im_end|>\n' }}
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{%- elif message.role == "tool" %}
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{%- if (loop.index0 == 0) 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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{{- message.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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{%- endif %}
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config.json
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{
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"architectures": [
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"Qwen2ForCausalLM"
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],
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"attention_dropout": 0.0,
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| 6 |
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"bos_token_id": null,
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"dtype": "float32",
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| 8 |
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"eos_token_id": 151645,
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| 9 |
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"hidden_act": "silu",
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| 10 |
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"hidden_size": 1536,
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"initializer_range": 0.02,
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| 12 |
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"intermediate_size": 8960,
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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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| 34 |
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"full_attention",
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"full_attention",
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"full_attention",
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| 37 |
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"full_attention",
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| 38 |
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"full_attention",
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| 39 |
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"full_attention",
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| 40 |
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"full_attention",
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| 41 |
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"full_attention"
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],
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| 43 |
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"max_position_embeddings": 32768,
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| 44 |
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"max_window_layers": 21,
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"model_type": "qwen2",
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| 46 |
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"num_attention_heads": 12,
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| 47 |
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"num_hidden_layers": 28,
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| 48 |
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"num_key_value_heads": 2,
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| 49 |
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"pad_token_id": 151643,
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| 50 |
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"rms_norm_eps": 1e-06,
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| 51 |
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"rope_parameters": {
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| 52 |
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"rope_theta": 1000000.0,
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| 53 |
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"rope_type": "default"
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| 54 |
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},
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| 55 |
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"sliding_window": null,
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| 56 |
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"tie_word_embeddings": true,
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| 57 |
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"transformers_version": "5.7.0",
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| 58 |
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"use_cache": false,
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| 59 |
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"use_sliding_window": false,
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| 60 |
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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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| 3 |
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"eos_token_id": [
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151645,
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| 5 |
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151643
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| 6 |
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],
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| 7 |
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"pad_token_id": 151643,
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| 8 |
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"repetition_penalty": 1.1,
|
| 9 |
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"temperature": 0.7,
|
| 10 |
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"top_k": 20,
|
| 11 |
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"top_p": 0.8,
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| 12 |
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"transformers_version": "5.7.0"
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| 13 |
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:f39923dff61262d67b9604ef12e9ed1ff2912b9a5c4c8d0bbb3ebfe287690317
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| 3 |
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size 6174895536
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:d7d178e226bf89c657a37a6b3eabd7ad166c763d3bd0018be4fa0037f212fc61
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size 11422156
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tokenizer_config.json
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{
|
| 2 |
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"add_prefix_space": false,
|
| 3 |
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"backend": "tokenizers",
|
| 4 |
+
"bos_token": null,
|
| 5 |
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"clean_up_tokenization_spaces": false,
|
| 6 |
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"eos_token": "<|im_end|>",
|
| 7 |
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"errors": "replace",
|
| 8 |
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"extra_special_tokens": [
|
| 9 |
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"<|im_start|>",
|
| 10 |
+
"<|im_end|>",
|
| 11 |
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"<|object_ref_start|>",
|
| 12 |
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"<|object_ref_end|>",
|
| 13 |
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"<|box_start|>",
|
| 14 |
+
"<|box_end|>",
|
| 15 |
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"<|quad_start|>",
|
| 16 |
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"<|quad_end|>",
|
| 17 |
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"<|vision_start|>",
|
| 18 |
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"<|vision_end|>",
|
| 19 |
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"<|vision_pad|>",
|
| 20 |
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"<|image_pad|>",
|
| 21 |
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"<|video_pad|>"
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| 22 |
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],
|
| 23 |
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"is_local": false,
|
| 24 |
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"local_files_only": false,
|
| 25 |
+
"model_max_length": 131072,
|
| 26 |
+
"pad_token": "<|endoftext|>",
|
| 27 |
+
"padding_side": "left",
|
| 28 |
+
"split_special_tokens": false,
|
| 29 |
+
"tokenizer_class": "Qwen2Tokenizer",
|
| 30 |
+
"truncation_side": "left",
|
| 31 |
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"unk_token": null
|
| 32 |
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}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:13296863c10f397f55241bb2932693f54dd147e2818252716a99bd5673cb0f8a
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| 3 |
+
size 6865
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