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Model: rudalson/Llama-3.2-3B-Instruct-KoAlpaca Source: Original Platform
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README.md
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README.md
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---
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library_name: transformers
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tags:
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- llama-3
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- koalpaca
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- korean
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- instruction-finetuning
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- sft
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language:
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- ko
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base_model: meta-llama/Llama-3.2-3B-Instruct
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datasets:
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- Taegyuu/KoAlpaca-v1.1a
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pipeline_tag: text-generation
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---
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# Llama-3.2-3B-KoAlpaca-Merged
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이 모델은 Meta의 **Llama-3.2-3B-Instruct** 모델을 베이스로 하여, 한국어 지시어 데이터셋인 **KoAlpaca v1.1a**를 학습(Fine-tuning)시킨 후 병합한 모델입니다. 한국어 질의응답 및 지시 이행 능력을 향상시키는 데 중점을 두었습니다.
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## Model Details
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### Model Description
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- **Model type:** Causal Language Model
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- **Language(s) (NLP):** 한국어 (Korean)
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- **License:** Llama 3.2 Community License
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- **Finetuned from model:** meta-llama/Llama-3.2-3B-Instruct
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- **Dataset:** Taegyuu/KoAlpaca-v1.1a
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## Uses
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### Direct Use
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이 모델은 한국어 질문에 답변하거나, 주어진 지시에 따라 텍스트를 생성하는 작업에 직접 사용할 수 있습니다.
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### Prompt Format (Llama 3.2)
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이 모델은 대화형 구조로 학습되었으므로 아래와 같은 메시지 형식을 권장합니다.
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```python
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messages = [
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{"role": "system", "content": "당신은 한국어 질의응답 전문가입니다. 주어진 문맥을 바탕으로 정확하고 간결한 답변을 제공하세요."},
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{"role": "user", "content": "인공지능이란 무엇인가요?"}
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]
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```
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## Training Hyperparameters
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The following hyperparameters were used during training:
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- **LoRA Specifics:**
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- r: 32
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- lora_alpha: 64
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- target_modules: All linear layers (q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj)
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- lora_dropout: 0.05
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- **Optimization:**
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- learning_rate: 2e-04
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- lr_scheduler_type: cosine
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- warmup_steps: 100
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- optimizer: AdamW
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- weight_decay: default (0.0)
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- **Training Strategy:**
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- num_train_epochs: 1
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- total_batch_size: 8 (2 per device * 4 accumulation steps)
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- gradient_checkpointing: True
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- fp16: True
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- neftune_noise_alpha: 5
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## Evaluation
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| Metric | Score |
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|-----|-----|
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| F1 Score | 11.40% |
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| ROUGE-1 | 4.94% |
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| ROUGE-L | 4.62% |
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## Support
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* SSAFY Tesla V100-PCIE-32GB
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chat_template.jinja
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chat_template.jinja
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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 = "" %}
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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 2023\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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{%- endif %}
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{{- "<|eot_id|>" }}
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{%- endif %}
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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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39
config.json
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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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"attention_dropout": 0.0,
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"bos_token_id": 128000,
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"eos_token_id": [
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128001,
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128008,
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128009
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 3072,
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"initializer_range": 0.02,
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"intermediate_size": 8192,
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"max_position_embeddings": 131072,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 24,
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"num_hidden_layers": 28,
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"num_key_value_heads": 8,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": {
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"factor": 32.0,
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"high_freq_factor": 4.0,
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"low_freq_factor": 1.0,
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"original_max_position_embeddings": 8192,
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"rope_type": "llama3"
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"rope_theta": 500000.0,
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"tie_word_embeddings": true,
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"torch_dtype": "float16",
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"transformers_version": "4.52.4",
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"use_cache": true,
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"vocab_size": 128256
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}
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generation_config.json
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generation_config.json
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"temperature": 0.6,
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"top_p": 0.9,
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"transformers_version": "4.52.4"
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}
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"model.layers.9.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.norm.weight": "model-00002-of-00002.safetensors"
|
||||
}
|
||||
}
|
||||
23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<|begin_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "<|eot_id|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|eot_id|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:9c85066e7642934ed09b44155e6566b0b5dab2637fb9433439ba5c9c7f8b50d3
|
||||
size 17210018
|
||||
2067
tokenizer_config.json
Normal file
2067
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user