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Model: kmseong/llama3_2_3b-instruct-WaRP_lr5e-5 Source: Original Platform
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83
README.md
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README.md
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---
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license: llama3.1
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language:
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- en
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library_name: transformers
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tags:
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- llama
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- safety
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- alignment
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- warp
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---
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# WaRP-Safety-Llama3_8B_Instruct
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Fine-tuned Llama 3.1 8B Instruct model for safety alignment using Weight space Rotation Process (WaRP).
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## Model Details
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- **Base Model**: meta-llama/Llama-3.1-8B-Instruct
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- **Training Method**: Safety-First WaRP (3-Phase pipeline)
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- **Training Date**: 2026-04-28
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## Training Procedure
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### Phase 1: Basis Construction
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- Collected activations from FFN layers using safety data
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- Computed SVD to obtain orthonormal basis vectors
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- Identified 419 important neurons in layer 31
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### Phase 2: Importance Scoring
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- Calculated importance scores using gradient-based methods
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- Generated masks for important directions
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- Used teacher forcing on safety responses
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### Phase 3: Incremental Learning
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- Fine-tuned on utility task (GSM8K) with gradient masking
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- Protected important directions to maintain safety
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- Improved utility while preserving safety mechanisms
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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 = "kmseong/WaRP-Safety-Llama3_8B_Instruct"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto", device_map="auto")
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# Generate text
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inputs = tokenizer("What is machine learning?", return_tensors="pt")
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outputs = model.generate(**inputs, max_length=100)
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print(tokenizer.decode(outputs[0]))
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```
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## Safety Features
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- ✅ Protected safety mechanisms through gradient masking
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- ✅ Maintained refusal capability for harmful requests
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- ✅ Improved utility on reasoning tasks
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- ✅ Balanced safety-utility tradeoff
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## Datasets
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- **Safety Data**: LibrAI/do-not-answer
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- **Utility Data**: openai/gsm8k
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## Citation
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```
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@article{warp-safety,
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title={Safety-First WaRP: Weight space Rotation Process for LLM Safety Alignment},
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author={Min-Seong Kim},
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year={2026}
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}
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```
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## License
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This model is built on Llama 3.1 8B Instruct and follows the same license.
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## Disclaimer
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This model is fine-tuned for improved safety. Users should evaluate model outputs for their specific use cases and apply additional safety measures as needed.
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93
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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"dtype": "float32",
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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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],
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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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},
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"rope_theta": 500000.0,
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"tie_word_embeddings": true,
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"transformers_version": "4.57.3",
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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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{
|
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"bos_token_id": 128000,
|
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"do_sample": true,
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"eos_token_id": [
|
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128009,
|
||||
128001,
|
||||
128008,
|
||||
128009
|
||||
],
|
||||
"pad_token_id": 128009,
|
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"temperature": 0.6,
|
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"top_p": 0.9,
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"transformers_version": "4.57.3"
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}
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11
model_metadata.json
Normal file
11
model_metadata.json
Normal file
@@ -0,0 +1,11 @@
|
||||
{
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||||
"model_id": "kmseong/llama3_2_3b-instruct-WaRP_lr5e-5",
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"base_model": "meta-llama/Llama-3.2-3B-Instruct",
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"training_method": "Safety-First WaRP",
|
||||
"upload_date": "2026-04-28T19:12:07.678205",
|
||||
"model_size_gb": 6.00033980794251,
|
||||
"important_neurons_layer31": 419,
|
||||
"keep_ratio": 0.1,
|
||||
"framework": "pytorch",
|
||||
"task": "text-generation"
|
||||
}
|
||||
16
special_tokens_map.json
Normal file
16
special_tokens_map.json
Normal file
@@ -0,0 +1,16 @@
|
||||
{
|
||||
"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
|
||||
}
|
||||
}
|
||||
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
Binary file not shown.
2062
tokenizer_config.json
Normal file
2062
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user