Training in progress, epoch 1
Browse files- README.md +58 -0
- chat_template.jinja +118 -0
- config.json +31 -0
- model.safetensors +3 -0
- runs/Jun18_08-35-43_ekl-Precision-7920-Tower/events.out.tfevents.1750203353.ekl-Precision-7920-Tower +3 -0
- special_tokens_map.json +23 -0
- tokenizer.json +0 -0
- tokenizer_config.json +705 -0
- training_args.bin +3 -0
README.md
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---
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base_model: KT-AI/Midm-2.0-Mini-Instruct
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library_name: transformers
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model_name: save_dir
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tags:
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- generated_from_trainer
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- trl
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- sft
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licence: license
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---
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# Model Card for save_dir
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This model is a fine-tuned version of [KT-AI/Midm-2.0-Mini-Instruct](https://huggingface.co/KT-AI/Midm-2.0-Mini-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="EUNKYEONG/save_dir", 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 SFT.
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### Framework versions
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- TRL: 0.9.6
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- Transformers: 4.52.4
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- Pytorch: 2.5.1
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- Datasets: 3.1.0
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- Tokenizers: 0.21.1
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## Citations
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Cite TRL as:
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```bibtex
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@misc{vonwerra2022trl,
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title = {{TRL: Transformer Reinforcement Learning}},
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author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
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year = 2020,
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journal = {GitHub repository},
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publisher = {GitHub},
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howpublished = {\url{https://github.com/huggingface/trl}}
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}
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```
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chat_template.jinja
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{%- macro eng_check(string) %}
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{%- for char in string %}
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{%- if char not in 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ1234567890`~!@#$%^&*()-_=+[{}]\;:",<.>/?
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' and char != "'" %}
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X
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{%- endif %}
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{%- endfor %}
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{%- endmacro %}
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{%- set in_message = messages[0]['content']|trim %}
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{%- set max_check_len = 20 %}
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{%- if in_message|length > max_check_len %}
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{%- set lang_check = in_message[:max_check_len] %}
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{%- else %}
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{%- set lang_check = in_message %}
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{%- endif %}
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{%- if eng_check(lang_check)|length == 0 %}
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{%- set default_system = 'Midm is an artificial intelligence-based service that responds kindly and safely.' %}
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{%- set locale = 0 %}
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{%- else %}
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{%- set default_system = 'Midm은 친절하고 안전하게 응답하는 인공지능 기반 서비스이다.' %}
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{%- set locale = 1 %}
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{%- endif %}
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{{- bos_token }}
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{%- if custom_tools is defined %}
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{%- set tools = custom_tools %}
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{%- endif %}
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{%- if not tools_in_user_message is defined %}
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{%- set tools_in_user_message = true %}
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{%- endif %}
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{%- if not date_string is defined %}
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{%- if strftime_now is defined %}
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{%- set date_string = strftime_now("%d %b %Y") %}
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{%- else %}
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{%- set date_string = "26 Jul 2024" %}
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{%- endif %}
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{%- endif %}
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{%- if not tools is defined %}
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{%- set tools = none %}
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{%- endif %}
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{#- This block extracts the system message, so we can slot it into the right place. #}
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{%- if messages[0]['role'] == 'system' %}
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{%- set system_message = messages[0]['content']|trim %}
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{%- set messages = messages[1:] %}
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{%- else %}
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{%- set system_message = default_system %}
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{%- endif %}
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{#- System message #}
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{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
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{%- if tools is not none %}
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{{- "Environment: ipython\n" }}
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{%- endif %}
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{{- "Cutting Knowledge Date: December 2024\n" }}
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{{- "Today Date: " + date_string + "\n\n" }}
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{%- if tools is not none and not tools_in_user_message %}
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{{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
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{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
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{{- "Do not use variables.\n\n" }}
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{%- for t in tools %}
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{{- t | tojson(indent=4) }}
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{{- "\n\n" }}
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{%- endfor %}
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{%- endif %}
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{{- system_message }}
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{{- "<|eot_id|>" }}
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{#- Custom tools are passed in a user message with some extra guidance #}
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{%- if tools_in_user_message and not tools is none %}
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{#- Extract the first user message so we can plug it in here #}
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{%- if messages | length != 0 %}
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{%- set first_user_message = messages[0]['content']|trim %}
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{%- set messages = messages[1:] %}
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{%- else %}
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{{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
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{%- endif %}
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{{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
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{{- "Given the following functions, please respond with a JSON for a function call " }}
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{{- "with its proper arguments that best answers the given prompt.\n\n" }}
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{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
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{{- "Do not use variables.\n\n" }}
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{%- for t in tools %}
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{{- t | tojson(indent=4) }}
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{{- "\n\n" }}
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{%- endfor %}
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{{- first_user_message + "<|eot_id|>"}}
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{%- endif %}
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{%- for message in messages %}
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{%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
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{{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
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{%- elif 'tool_calls' in message %}
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{%- if not message.tool_calls|length == 1 %}
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{{- raise_exception("This model only supports single tool-calls at once!") }}
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{%- endif %}
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{%- set tool_call = message.tool_calls[0].function %}
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{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
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{{- '{"name": "' + tool_call.name + '", ' }}
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{{- '"parameters": ' }}
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{{- tool_call.arguments | tojson }}
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{{- "}" }}
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{{- "<|eot_id|>" }}
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{%- elif message.role == "tool" or message.role == "ipython" %}
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{{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
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{%- if message.content is mapping or message.content is iterable %}
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{{- message.content | tojson }}
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{%- else %}
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{{- message.content }}
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| 112 |
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{%- endif %}
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{{- "<|eot_id|>" }}
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| 114 |
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{%- endif %}
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| 115 |
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{%- endfor %}
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{%- if add_generation_prompt %}
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{{- '<|start_header_id|>assistant<|end_header_id|>\n\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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"LlamaForCausalLM"
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],
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"attention_bias": false,
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| 6 |
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"attention_dropout": 0.0,
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| 7 |
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"attention_probs_dropout_prob": 0.1,
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| 8 |
+
"bos_token_id": null,
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| 9 |
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"eos_token_id": 2,
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| 10 |
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"head_dim": 128,
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| 11 |
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"hidden_act": "silu",
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| 12 |
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"hidden_dropout_prob": 0.0,
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| 13 |
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"hidden_size": 1792,
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| 14 |
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"initializer_range": 0.02,
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| 15 |
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"intermediate_size": 4608,
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| 16 |
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"max_position_embeddings": 65536,
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| 17 |
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"mlp_bias": false,
|
| 18 |
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"model_type": "llama",
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| 19 |
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"num_attention_heads": 32,
|
| 20 |
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"num_hidden_layers": 48,
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| 21 |
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"num_key_value_heads": 8,
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| 22 |
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"pretraining_tp": 1,
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| 23 |
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"rms_norm_eps": 1e-05,
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| 24 |
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"rope_scaling": null,
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| 25 |
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"rope_theta": 8000000,
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| 26 |
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"tie_word_embeddings": true,
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| 27 |
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"torch_dtype": "bfloat16",
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| 28 |
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"transformers_version": "4.52.4",
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"use_cache": true,
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| 30 |
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"vocab_size": 131392
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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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oid sha256:e635371405d2fd7370329cc0b3f8affad79965a75d24862c755d3f06dd72130a
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| 3 |
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size 4611084960
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runs/Jun18_08-35-43_ekl-Precision-7920-Tower/events.out.tfevents.1750203353.ekl-Precision-7920-Tower
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version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:89675be041ac2fc7e4695b2e741031fffa6e850f879b21093b05d1eb3d2b766d
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| 3 |
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size 8755
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special_tokens_map.json
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{
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| 2 |
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"bos_token": {
|
| 3 |
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"content": "<|begin_of_text|>",
|
| 4 |
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"lstrip": false,
|
| 5 |
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"normalized": false,
|
| 6 |
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"rstrip": false,
|
| 7 |
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"single_word": false
|
| 8 |
+
},
|
| 9 |
+
"eos_token": {
|
| 10 |
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"content": "<|eot_id|>",
|
| 11 |
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"lstrip": false,
|
| 12 |
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"normalized": false,
|
| 13 |
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"rstrip": false,
|
| 14 |
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"single_word": false
|
| 15 |
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},
|
| 16 |
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"pad_token": {
|
| 17 |
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"content": "<|end_of_text|>",
|
| 18 |
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"lstrip": false,
|
| 19 |
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"normalized": false,
|
| 20 |
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"rstrip": false,
|
| 21 |
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"single_word": false
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| 22 |
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}
|
| 23 |
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}
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tokenizer.json
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tokenizer_config.json
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| 1 |
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{
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| 2 |
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|
| 3 |
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| 7 |
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| 8 |
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| 9 |
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"special": true
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| 10 |
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},
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| 11 |
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"1": {
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| 12 |
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|
| 13 |
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| 14 |
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|
| 15 |
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"rstrip": false,
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| 16 |
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|
| 17 |
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"special": true
|
| 18 |
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},
|
| 19 |
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"2": {
|
| 20 |
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"content": "<|end_of_text|>",
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| 21 |
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| 22 |
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| 23 |
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| 24 |
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| 25 |
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"special": true
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| 26 |
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},
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| 27 |
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"131301": {
|
| 28 |
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"content": "<|eot_id|>",
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| 29 |
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| 30 |
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| 31 |
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| 32 |
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| 33 |
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| 34 |
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| 35 |
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|
| 36 |
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| 37 |
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| 38 |
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| 39 |
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| 44 |
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| 60 |
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| 68 |
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| 69 |
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| 72 |
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| 73 |
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| 74 |
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| 75 |
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|
| 76 |
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| 77 |
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| 78 |
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| 79 |
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| 80 |
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| 81 |
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| 82 |
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| 83 |
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|
| 84 |
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| 85 |
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| 90 |
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| 92 |
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| 93 |
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| 95 |
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| 96 |
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| 97 |
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| 98 |
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| 99 |
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|
| 100 |
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| 101 |
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| 103 |
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| 104 |
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| 106 |
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| 107 |
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"131311": {
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},
|
| 555 |
+
"131367": {
|
| 556 |
+
"content": "#@ID@#",
|
| 557 |
+
"lstrip": false,
|
| 558 |
+
"normalized": false,
|
| 559 |
+
"rstrip": false,
|
| 560 |
+
"single_word": false,
|
| 561 |
+
"special": true
|
| 562 |
+
},
|
| 563 |
+
"131368": {
|
| 564 |
+
"content": "#@주민번호@#",
|
| 565 |
+
"lstrip": false,
|
| 566 |
+
"normalized": false,
|
| 567 |
+
"rstrip": false,
|
| 568 |
+
"single_word": false,
|
| 569 |
+
"special": true
|
| 570 |
+
},
|
| 571 |
+
"131369": {
|
| 572 |
+
"content": "#@이메일@#",
|
| 573 |
+
"lstrip": false,
|
| 574 |
+
"normalized": false,
|
| 575 |
+
"rstrip": false,
|
| 576 |
+
"single_word": false,
|
| 577 |
+
"special": true
|
| 578 |
+
},
|
| 579 |
+
"131370": {
|
| 580 |
+
"content": "#@계좌번호@#",
|
| 581 |
+
"lstrip": false,
|
| 582 |
+
"normalized": false,
|
| 583 |
+
"rstrip": false,
|
| 584 |
+
"single_word": false,
|
| 585 |
+
"special": true
|
| 586 |
+
},
|
| 587 |
+
"131371": {
|
| 588 |
+
"content": "#@전화번호@#",
|
| 589 |
+
"lstrip": false,
|
| 590 |
+
"normalized": false,
|
| 591 |
+
"rstrip": false,
|
| 592 |
+
"single_word": false,
|
| 593 |
+
"special": true
|
| 594 |
+
},
|
| 595 |
+
"131372": {
|
| 596 |
+
"content": "#@주소@#",
|
| 597 |
+
"lstrip": false,
|
| 598 |
+
"normalized": false,
|
| 599 |
+
"rstrip": false,
|
| 600 |
+
"single_word": false,
|
| 601 |
+
"special": true
|
| 602 |
+
},
|
| 603 |
+
"131373": {
|
| 604 |
+
"content": "#@자동차번호@#",
|
| 605 |
+
"lstrip": false,
|
| 606 |
+
"normalized": false,
|
| 607 |
+
"rstrip": false,
|
| 608 |
+
"single_word": false,
|
| 609 |
+
"special": true
|
| 610 |
+
},
|
| 611 |
+
"131374": {
|
| 612 |
+
"content": "#@사업자등록번호@#",
|
| 613 |
+
"lstrip": false,
|
| 614 |
+
"normalized": false,
|
| 615 |
+
"rstrip": false,
|
| 616 |
+
"single_word": false,
|
| 617 |
+
"special": true
|
| 618 |
+
},
|
| 619 |
+
"131375": {
|
| 620 |
+
"content": "#@자동차운전면허번호@#",
|
| 621 |
+
"lstrip": false,
|
| 622 |
+
"normalized": false,
|
| 623 |
+
"rstrip": false,
|
| 624 |
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"single_word": false,
|
| 625 |
+
"special": true
|
| 626 |
+
},
|
| 627 |
+
"131376": {
|
| 628 |
+
"content": "#@여권번호@#",
|
| 629 |
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"lstrip": false,
|
| 630 |
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"normalized": false,
|
| 631 |
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"rstrip": false,
|
| 632 |
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"single_word": false,
|
| 633 |
+
"special": true
|
| 634 |
+
},
|
| 635 |
+
"131377": {
|
| 636 |
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"content": "#@외국인등록번호@#",
|
| 637 |
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"lstrip": false,
|
| 638 |
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"normalized": false,
|
| 639 |
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"rstrip": false,
|
| 640 |
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"single_word": false,
|
| 641 |
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"special": true
|
| 642 |
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},
|
| 643 |
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"131378": {
|
| 644 |
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"content": "#@건보번호@#",
|
| 645 |
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"lstrip": false,
|
| 646 |
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"normalized": false,
|
| 647 |
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"rstrip": false,
|
| 648 |
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"single_word": false,
|
| 649 |
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"special": true
|
| 650 |
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},
|
| 651 |
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"131379": {
|
| 652 |
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"content": "#@신용카드번호@#",
|
| 653 |
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"lstrip": false,
|
| 654 |
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"normalized": false,
|
| 655 |
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"rstrip": false,
|
| 656 |
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"single_word": false,
|
| 657 |
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"special": true
|
| 658 |
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},
|
| 659 |
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"131380": {
|
| 660 |
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"content": "#@IP@#",
|
| 661 |
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"lstrip": false,
|
| 662 |
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"normalized": false,
|
| 663 |
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"rstrip": false,
|
| 664 |
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"single_word": false,
|
| 665 |
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"special": true
|
| 666 |
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},
|
| 667 |
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"131381": {
|
| 668 |
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"content": "#@MAC주소@#",
|
| 669 |
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"lstrip": false,
|
| 670 |
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"normalized": false,
|
| 671 |
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"rstrip": false,
|
| 672 |
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"single_word": false,
|
| 673 |
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"special": true
|
| 674 |
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},
|
| 675 |
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"131382": {
|
| 676 |
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"content": "#@SNS계정@#",
|
| 677 |
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"lstrip": false,
|
| 678 |
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"normalized": false,
|
| 679 |
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"rstrip": false,
|
| 680 |
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"single_word": false,
|
| 681 |
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"special": true
|
| 682 |
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},
|
| 683 |
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"131383": {
|
| 684 |
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"content": "#@통관번호#",
|
| 685 |
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"lstrip": false,
|
| 686 |
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"normalized": false,
|
| 687 |
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"rstrip": false,
|
| 688 |
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"single_word": false,
|
| 689 |
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"special": true
|
| 690 |
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}
|
| 691 |
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},
|
| 692 |
+
"bos_token": "<|begin_of_text|>",
|
| 693 |
+
"clean_up_tokenization_spaces": true,
|
| 694 |
+
"content": "<|end_of_text|>",
|
| 695 |
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"eos_token": "<|eot_id|>",
|
| 696 |
+
"extra_special_tokens": {},
|
| 697 |
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"legacy": false,
|
| 698 |
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"lstrip": false,
|
| 699 |
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"model_max_length": 1000000000000000019884624838656,
|
| 700 |
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"normalized": false,
|
| 701 |
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"pad_token": "<|end_of_text|>",
|
| 702 |
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"rstrip": false,
|
| 703 |
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"single_word": false,
|
| 704 |
+
"tokenizer_class": "PreTrainedTokenizer"
|
| 705 |
+
}
|
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:aa48ffc091fc58eaf63e1f0e636c910bdfc4cc0d4bca8cdd0de0a6e0da8ec851
|
| 3 |
+
size 5624
|