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Model: jamesjk4242/insighta-mandala-v13 Source: Original Platform
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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insighta-mandala-v13-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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insighta-mandala-v13-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
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README.md
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README.md
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---
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pipeline_tag: text-generation
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library_name: transformers
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tags:
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- qwen3
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- gguf
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- mandala
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- education
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- fine-tuned
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language:
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- ko
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- en
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license: apache-2.0
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---
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# Insighta Mandala v13
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Fine-tuned Qwen3-4B model for generating mandala learning plans in JSON format.
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## Model Details
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- **Base model**: Qwen/Qwen3-4B
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- **Fine-tuning**: LoRA on mandala learning plan generation task
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- **Languages**: Korean, English
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- **Output format**: Structured JSON (mandala chart format)
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## Available Quantizations
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| Format | Size | Description |
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|--------|------|-------------|
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| `model.safetensors` | ~8GB | Full F16 weights |
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| `insighta-mandala-v13-Q8_0.gguf` | ~4GB | Q8_0 quantized GGUF |
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| `insighta-mandala-v13-Q4_K_M.gguf` | ~2.4GB | Q4_K_M quantized GGUF (recommended for CPU) |
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## Usage
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### With llama-cpp-python
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```python
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from llama_cpp import Llama
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llm = Llama(model_path="insighta-mandala-v13-Q4_K_M.gguf", n_ctx=4096)
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output = llm(
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"<|im_start|>user\nTOEFL 100점 만다라트 차트를 만들어줘<|im_end|>\n<|im_start|>assistant\n",
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max_tokens=2048,
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temperature=0.7,
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)
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print(output["choices"][0]["text"])
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```
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### With HF Space API
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```bash
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curl -X POST https://jamesjk4242-insighta-mandala-v13-api.hf.space/api/predict \
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-H "Content-Type: application/json" \
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-d '{"data": ["TOEFL 100점 만다라트 차트를 만들어줘", "You are a helpful assistant that generates mandala learning plans in JSON format.", 2048, 0.7, 0.9, true]}'
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```
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chat_template.jinja
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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 + '\n\n' }}
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{%- endif %}
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{{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
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{%- else %}
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{%- if messages[0].role == 'system' %}
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{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
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{%- for forward_message in messages %}
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{%- set index = (messages|length - 1) - loop.index0 %}
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{%- set message = messages[index] %}
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{%- set tool_start = '<tool_response>' %}
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{%- set tool_start_length = tool_start|length %}
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{%- set start_of_message = message.content[:tool_start_length] %}
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{%- set tool_end = '</tool_response>' %}
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{%- set tool_end_length = tool_end|length %}
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{%- set start_pos = (message.content|length) - tool_end_length %}
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{%- if start_pos < 0 %}
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{%- set start_pos = 0 %}
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{%- endif %}
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{%- set end_of_message = message.content[start_pos:] %}
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{%- if ns.multi_step_tool and message.role == "user" and not(start_of_message == tool_start and end_of_message == tool_end) %}
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{%- set ns.multi_step_tool = false %}
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{%- set ns.last_query_index = index %}
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{%- endif %}
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{%- endfor %}
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{%- for message in messages %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
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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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{%- set content = message.content %}
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{%- set reasoning_content = '' %}
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{%- if message.reasoning_content is defined and message.reasoning_content is not none %}
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{%- set reasoning_content = message.reasoning_content %}
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{%- else %}
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{%- if '</think>' in message.content %}
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{%- set content = (message.content.split('</think>')|last).lstrip('\n') %}
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{%- set reasoning_content = (message.content.split('</think>')|first).rstrip('\n') %}
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{%- set reasoning_content = (reasoning_content.split('<think>')|last).lstrip('\n') %}
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{%- endif %}
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{%- endif %}
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{%- if loop.index0 > ns.last_query_index %}
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{%- if loop.last or (not loop.last and reasoning_content) %}
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{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
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{%- else %}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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{%- endif %}
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{%- else %}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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{%- endif %}
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{%- if message.tool_calls %}
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{%- for tool_call in message.tool_calls %}
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{%- if (loop.first and content) or (not loop.first) %}
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{{- '\n' }}
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{%- endif %}
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{%- if tool_call.function %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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{{- '<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
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{{- '", "arguments": ' }}
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{%- if tool_call.arguments is string %}
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{{- tool_call.arguments }}
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{%- else %}
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{{- tool_call.arguments | tojson }}
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{%- endif %}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{%- endif %}
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{{- '<|im_end|>\n' }}
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{%- elif message.role == "tool" %}
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{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
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{{- '<|im_start|>user' }}
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{%- endif %}
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{{- '\n<tool_response>\n' }}
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{{- 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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{%- if enable_thinking is defined and enable_thinking is false %}
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{{- '<think>\n\n</think>\n\n' }}
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{%- endif %}
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{%- endif %}
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config.json
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config.json
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{
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"architectures": [
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"Qwen3ForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 151643,
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"dtype": "float16",
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"eos_token_id": 151645,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 2560,
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"initializer_range": 0.02,
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"intermediate_size": 9728,
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"layer_types": [
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention"
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],
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"max_position_embeddings": 40960,
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"max_window_layers": 36,
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"model_type": "qwen3",
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"num_attention_heads": 32,
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"num_hidden_layers": 36,
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"num_key_value_heads": 8,
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"pad_token_id": null,
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"rms_norm_eps": 1e-06,
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"rope_parameters": {
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"rope_theta": 1000000,
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"rope_type": "default"
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},
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"sliding_window": null,
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"tie_word_embeddings": true,
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"transformers_version": "5.5.0",
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"use_cache": true,
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"use_sliding_window": false,
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"vocab_size": 151936
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}
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generation_config.json
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generation_config.json
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{
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"bos_token_id": 151643,
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"do_sample": true,
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"eos_token_id": [
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151645,
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151643
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],
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"pad_token_id": 151643,
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"temperature": 0.6,
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"top_k": 20,
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"top_p": 0.95,
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"transformers_version": "5.5.0"
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}
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insighta-mandala-v13-Q4_K_M.gguf
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insighta-mandala-v13-Q4_K_M.gguf
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version https://git-lfs.github.com/spec/v1
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|
oid sha256:4a66edd9572256793cc863caecd6b52e6213b3ac1d08767ad6b6186b87baa5aa
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size 2497280800
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insighta-mandala-v13-Q8_0.gguf
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3
insighta-mandala-v13-Q8_0.gguf
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version https://git-lfs.github.com/spec/v1
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||||||
|
oid sha256:8e4a2453a542fa3417793ec5ad721b6f7e9d3013b823370b04fc96a4666043a4
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|
size 4280405280
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model.safetensors
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model.safetensors
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version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:dec9242dce28d364da25be5ebdeb4378d250ce317c36ee310f42f48511c895ef
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size 8044981680
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tokenizer.json
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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|
oid sha256:d7430e9138b76e93fb6f93462394d236b411111aef53cb421ba97d2691040cca
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|
size 11423114
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tokenizer_config.json
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tokenizer_config.json
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{
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"add_prefix_space": false,
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"backend": "tokenizers",
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"bos_token": null,
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"clean_up_tokenization_spaces": false,
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"eos_token": "<|im_end|>",
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"errors": "replace",
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"is_local": true,
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"model_max_length": 40960,
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"pad_token": "<|PAD_TOKEN|>",
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"padding_side": "left",
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"split_special_tokens": false,
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"tokenizer_class": "Qwen2Tokenizer",
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"unk_token": null
|
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}
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Reference in New Issue
Block a user