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Model: sdavies/globe-theatre-qwen25-3b-merged Source: Original Platform
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README.md
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README.md
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---
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license: apache-2.0
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base_model:
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- Qwen/Qwen2.5-3B-Instruct
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tags:
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- qwen2.5
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- transformers
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- comedy
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- creative-writing
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- shakespeare
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- merged
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- text-generation-inference
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- hackathon
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- build-small
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library_name: transformers
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---
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# 🎭 The Tragedy of the Group Chat: Merged Model
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A standalone merged Transformers version of The Tragedy of the Group Chat.
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This repository combines the Qwen2.5-3B-Instruct base model with the trained LoRA adapter into a single deployable **Transformers** model.
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**Most language models try to solve your problems.**
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**The Tragedy of the Group Chat** assumes your problems deserve a **badly performed Elizabethan stage production** instead.
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> You forgot to buy milk. Again. Everyone is angry. A sensible person would apologise.
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> This model instead assembles an Elizabethan comedy troupe to make the situation considerably worse.
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## About the project
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The Tragedy of the Group Chat was created for the Hugging Face Build-Small Hackathon (June 2026).
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The project explored how much personality and structure can be taught to a relatively small local model through careful fine-tuning and iterative evaluation.
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Rather than building a general-purpose assistant, the goal was to transform tiny modern inconveniences into exaggerated theatrical comedy scenes.
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## Repository structure
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The project consists of three related repositories:
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- **LoRA adapter**: The original PEFT fine-tuning.<br>
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- **Merged model (this repository)**: A standalone Transformers version of the model. <br>
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- **GGUF edition**: A quantised deployment build for llama.cpp and local inference.
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## What does it do?
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Given a small modern grievance, the model produces a short comic scene in the style of a badly organised Elizabethan theatre company.
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Typical outputs include:
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* TITLE
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* DRAMATIS PERSONAE
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* SCENE
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* THOU MUST CHOOSE
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The intended voice combines influences from:
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* Shakespeare
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* Blackadder
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* Monty Python
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* British sitcoms
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* Amateur dramatic societies
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## Performance
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The underlying fine-tuned model achieved **56/80** on a held-out ten-prompt manual benchmark. The base Qwen2.5-3B-Instruct model scored **36/80** using the same evaluation procedure.
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The merged model preserves the behaviour of the LoRA adapter while simplifying deployment.
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## Intended use
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The model is intended for entertainment and creative text generation.
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It performs best on:
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* everyday annoyances
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* social awkwardness
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* household disasters
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* transport failures
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* office politics
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* mildly haunted appliances
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* inexplicably judgemental animals
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## Limitations
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The model intentionally prioritises style over factual accuracy.
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Recurring characters and running jokes are expected behaviour.
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The model performs best on small frustrations rather than major life events.
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## Loading
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This repository contains a standalone Transformers model and can be loaded directly with the Hugging Face Transformers library.
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## Build process
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This model was created by:
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Qwen2.5-3B-Instruct
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↓
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LoRA fine-tuning
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↓
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PEFT merge-and-unload
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↓
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Standalone Transformers model
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This merged model serves as the source for the GGUF deployment build.
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## Try the model
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- 🎭 [Interactive demo](https://huggingface.co/spaces/sdavies/tragedy-of-the-group-chat)
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## Related repositories
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- [LoRA adapter](https://huggingface.co/sdavies/globe-theatre-qwen25-3b-lora)
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- [GGUF edition](https://huggingface.co/sdavies/globe-theatre-qwen25-3b-gguf)
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54
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'] }}
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{%- else %}
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{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
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{%- endif %}
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{{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
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{%- else %}
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{%- if messages[0]['role'] == 'system' %}
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{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
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{%- else %}
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{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- for message in messages %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
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{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{{- '<|im_start|>' + message.role }}
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{%- if message.content %}
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{{- '\n' + message.content }}
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{%- endif %}
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{%- for tool_call in message.tool_calls %}
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{%- if tool_call.function is defined %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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{{- '\n<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
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{{- '", "arguments": ' }}
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{{- tool_call.arguments | tojson }}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{{- '<|im_end|>\n' }}
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{%- elif message.role == "tool" %}
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{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
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{{- '<|im_start|>user' }}
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{%- endif %}
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{{- '\n<tool_response>\n' }}
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{{- message.content }}
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{{- '\n</tool_response>' }}
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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{{- '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- endfor %}
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{%- if add_generation_prompt %}
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{{- '<|im_start|>assistant\n' }}
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{%- endif %}
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69
config.json
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config.json
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{
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"architectures": [
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"Qwen2ForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 151643,
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"dtype": "float16",
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"eos_token_id": 151645,
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"hidden_act": "silu",
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"hidden_size": 2048,
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"initializer_range": 0.02,
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"intermediate_size": 11008,
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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": 32768,
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"max_window_layers": 70,
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"model_type": "qwen2",
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"num_attention_heads": 16,
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"num_hidden_layers": 36,
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"num_key_value_heads": 2,
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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": 1000000.0,
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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": "5.10.2",
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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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14
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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"pad_token_id": 151643,
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"repetition_penalty": 1.05,
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"temperature": 0.7,
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"top_k": 20,
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"top_p": 0.8,
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"transformers_version": "5.10.2"
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}
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model.safetensors
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 6171926680
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3
tokenizer.json
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3
tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:3fd169731d2cbde95e10bf356d66d5997fd885dd8dbb6fb4684da3f23b2585d8
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size 11421892
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30
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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"extra_special_tokens": [
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"<|im_start|>",
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"<|object_ref_start|>",
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"<|object_ref_end|>",
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"<|box_start|>",
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"<|box_end|>",
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"<|quad_start|>",
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"<|quad_end|>",
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"<|vision_start|>",
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"<|vision_end|>",
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"<|vision_pad|>",
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"<|image_pad|>",
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"<|video_pad|>"
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],
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"is_local": false,
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"local_files_only": false,
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"model_max_length": 131072,
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"pad_token": "<|endoftext|>",
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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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