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Model: Pranavz/qwen-4b-2507-rp-mahou 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: Qwen/Qwen3-4B-Instruct-2507
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tags:
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- roleplay
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- creative-writing
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- sft
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- qwen3
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datasets:
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- flammenai/flame-kindling-v1
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language:
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- en
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pipeline_tag: text-generation
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library_name: transformers
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---
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# qwen-4b-2507-rp-mahou
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A full-parameter SFT of [`Qwen/Qwen3-4B-Instruct-2507`](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507) on [`flammenai/flame-kindling-v1`](https://huggingface.co/datasets/flammenai/flame-kindling-v1) for creative roleplay and character interaction.
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## Highlights
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- Base: Qwen3-4B-Instruct-2507
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- Method: full-sequence SFT (no LoRA)
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- Dataset: flame-kindling-v1 (RP / creative writing)
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- Precision: bf16
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- Chat template: Qwen3 (use `enable_thinking=False` for RP)
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## Usage
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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MODEL_ID = "Pranavz/qwen-4b-2507-rp-mahou"
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tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
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model = AutoModelForCausalLM.from_pretrained(
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MODEL_ID,
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torch_dtype=torch.bfloat16,
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device_map="auto",
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)
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messages = [
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{"role": "system", "content": "You are a creative roleplay assistant. Stay in character, write vividly, and use asterisks for actions."},
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{"role": "user", "content": "*walks into the tavern, shaking off the rain* Evening, barkeep. Got a room?"},
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]
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True,
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enable_thinking=False,
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)
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inputs = tokenizer(text, return_tensors="pt").to(model.device)
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with torch.inference_mode():
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out = model.generate(
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**inputs,
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max_new_tokens=512,
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temperature=0.8,
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top_p=0.9,
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top_k=40,
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repetition_penalty=1.1,
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do_sample=True,
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)
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print(tokenizer.decode(out[0][inputs.input_ids.shape[1]:], skip_special_tokens=True))
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```
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## Recommended sampler settings
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| Parameter | Value | Notes |
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|---|---|---|
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| `temperature` | 0.7 – 0.85 | creative without going off-rails |
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| `top_p` | 0.9 | trim the long tail |
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| `top_k` | 40 | hard vocab cap |
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| `min_p` | 0.05 | optional, often nicer than top_p alone |
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| `repetition_penalty` | 1.05 – 1.15 | RP models love loops — kill them |
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| `max_new_tokens` | 512 – 1024 | RP needs room |
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Always pass `enable_thinking=False` to the chat template — RP doesn't want CoT.
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## Limitations
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- Trained on a single curated RP dataset; expect a particular tone (vivid, action-asterisk style)
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- Not safety-tuned beyond what the base model provides
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- English only
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## Acknowledgements
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- Base model: [Qwen team](https://huggingface.co/Qwen)
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- Dataset: [flammenai/flame-kindling-v1](https://huggingface.co/datasets/flammenai/flame-kindling-v1)
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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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{%- for message in messages %}
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{%- if message.content is string %}
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{%- set content = message.content %}
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{%- else %}
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{%- set content = '' %}
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{%- endif %}
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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' + content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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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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{{- 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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71
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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"hidden_act": "silu",
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"hidden_size": 2560,
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"initializer_range": 0.02,
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],
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"max_position_embeddings": 262144,
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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_key_value_heads": 8,
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"rms_norm_eps": 1e-06,
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"rope_parameters": {
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"rope_type": "default"
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"use_cache": false,
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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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