nisha1990kum

Qwen3.5-Hasutsubomi-9B

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README

License: apache-2.0

Model Highlights

Japanese Sub-Culture Expert: Little knowledge of Japanese internet lore, anime tropes, and light novel storytelling structures.
Creative Writing Focus: Fine-tuned to generate better-quality prose, character dialogues, and world-building outlines.
Keep Vision-Language Capabilities: Inherited from the Qwen3.5 base, Hasutsubomi can (hopefully) analyze anime illustrations, manga panels and write stories or descriptions based on them.
Pre-Alpha State: This is an early checkpoint release. Expect highly creative but occasionally unstable outputs as the model continues to learn.
Efficient Architecture: Powered by Qwen3.5's Gated Delta Networks and sparse Mixture-of-Experts for high-throughput generation.

Model Overview

Type: Causal Language Model with Vision Encoder
Base Model: Qwen/Qwen3.5-9B
Fine-tuning Stage: Pre-Alpha (Work in Progress)
Primary Languages: Japanese, English
Number of Parameters: 9B
Hidden Dimension: 4096
Number of Layers: 32
Context Length: Natively supports up to 262,144 tokens (excellent for long-form light novel generation or context-heavy RP).

Intended Use

Direct Use Cases

Story Generation: Writing light novel chapters, fanfiction, or visual novel scripts.
Image-to-Story: Uploading a character illustration and asking the model to write a backstory or describe the character's design.
Cultural Explanation: Explaining complex or niche Japanese anime history, or manga tropes. (limited performance for now)

Limitations & Biases (Pre-Alpha)

As a pre-alpha checkpoint, the model may occasionally suffer from formatting instability or repetitive phrasing in extended writing tasks.
It might heavily lean into dramatic or stereotypical anime tropes even when a neutral tone is requested.
Hallucinations may occur when asked about highly obscure, real-world sub-culture events.

Quickstart

Because Qwen3.5 models operate in a "thinking mode" by default, Hasutsubomi will often draft its creative thoughts or plot outlines before writing the final response.

Below is a guide to using the model via the OpenAI-compatible API format (assuming you are serving the model via vLLM, SGLang, or standard Transformers).

Creative Writing (Text-Only)

python

from openai import OpenAI# Configured by environment variablesclient = OpenAI(base_url="http://localhost:8000/v1", api_key="EMPTY") messages =[    {"role": "system", "content": "You are a professional Japanese light novel author."},    {"role": "user", "content": "Write a short prologue for a fantasy Isekai story where the protagonist is reincarnated not as a hero, but as a magical library. Use an atmospheric and slightly melancholic tone in Japanese."}] chat_response = client.chat.completions.create(    model="Local-Novel-LLM-project/Qwen3.5-Hasutsubomi-9B",    messages=messages,    max_tokens=4096,    temperature=0.8, # Slightly higher temperature for creative writing    top_p=0.9,    presence_penalty=1.5,)print("Chat response:", chat_response.choices[0].message.content)

Analyzing Anime/Manga Art (Vision-Language)

python

from openai import OpenAI client = OpenAI(base_url="http://localhost:8000/v1", api_key="EMPTY") messages = [    {        "role": "user",        "content":[            {                "type": "image_url",                "image_url": {                    "url": "https://example.com/anime_character_design.jpg"                }            },            {                "type": "text",                "text": "Analyze this character's design. Based on typical Japanese sub-culture tropes, what kind of personality (e.g., Tsundere, Yandere, Chuunibyou) do they likely have, and what kind of magic would they use in a fantasy setting?"            }        ]    }] chat_response = client.chat.completions.create(    model="Local-Novel-LLM-project/Qwen3.5-Hasutsubomi-9B",    messages=messages,    max_tokens=2048,    temperature=0.7,)print("Chat response:", chat_response.choices[0].message.content)

Best Practices for Hasutsubomi

Prompting for Writing: When asking the model to write stories, it helps to explicitly state the desired trope or genre (e.g., "Cyberpunk", "Isekai", "Slice of Life", "Iyashikei").
Sampling Parameters for Creativity:
- For creative writing and roleplay, we recommend a higher temperature: temperature=0.8 to 1.0 with a top_p=0.9.
- Apply a slight presence_penalty=1.5 to encourage varied vocabulary.
Thinking Mode: Allow the model to utilize <think>\n...\</think> tags to plan out story beats before it generates the final text. This significantly improves narrative coherence.

Citation

If you use this fine-tuned model, please consider acknowledging this repository. Additionally, please cite the original Qwen3.5 paper:

bibtex

@misc{qwen3.5,    title  = {{Qwen3.5}: Towards Native Multimodal Agents},    author = {{Qwen Team}},    month  = {February},    year   = {2026},    url    = {https://qwen.ai/blog?id=qwen3.5}}

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Model Details

Model Provider

nisha1990kum

Model Tree

Base

Qwen/Qwen3.5-9B

Fine-tuned

this model

Input Modalities

TextImageVideo

Output Modalities

Text

Supported Functionality

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README

License: apache-2.0

Model Highlights

Japanese Sub-Culture Expert: Little knowledge of Japanese internet lore, anime tropes, and light novel storytelling structures.
Creative Writing Focus: Fine-tuned to generate better-quality prose, character dialogues, and world-building outlines.
Keep Vision-Language Capabilities: Inherited from the Qwen3.5 base, Hasutsubomi can (hopefully) analyze anime illustrations, manga panels and write stories or descriptions based on them.
Pre-Alpha State: This is an early checkpoint release. Expect highly creative but occasionally unstable outputs as the model continues to learn.
Efficient Architecture: Powered by Qwen3.5's Gated Delta Networks and sparse Mixture-of-Experts for high-throughput generation.

Model Overview

Type: Causal Language Model with Vision Encoder
Base Model: Qwen/Qwen3.5-9B
Fine-tuning Stage: Pre-Alpha (Work in Progress)
Primary Languages: Japanese, English
Number of Parameters: 9B
Hidden Dimension: 4096
Number of Layers: 32
Context Length: Natively supports up to 262,144 tokens (excellent for long-form light novel generation or context-heavy RP).

Intended Use

Direct Use Cases

Story Generation: Writing light novel chapters, fanfiction, or visual novel scripts.
Image-to-Story: Uploading a character illustration and asking the model to write a backstory or describe the character's design.
Cultural Explanation: Explaining complex or niche Japanese anime history, or manga tropes. (limited performance for now)

Limitations & Biases (Pre-Alpha)

As a pre-alpha checkpoint, the model may occasionally suffer from formatting instability or repetitive phrasing in extended writing tasks.
It might heavily lean into dramatic or stereotypical anime tropes even when a neutral tone is requested.
Hallucinations may occur when asked about highly obscure, real-world sub-culture events.

Quickstart

Because Qwen3.5 models operate in a "thinking mode" by default, Hasutsubomi will often draft its creative thoughts or plot outlines before writing the final response.

Below is a guide to using the model via the OpenAI-compatible API format (assuming you are serving the model via vLLM, SGLang, or standard Transformers).

Creative Writing (Text-Only)

python

from openai import OpenAI# Configured by environment variablesclient = OpenAI(base_url="http://localhost:8000/v1", api_key="EMPTY") messages =[    {"role": "system", "content": "You are a professional Japanese light novel author."},    {"role": "user", "content": "Write a short prologue for a fantasy Isekai story where the protagonist is reincarnated not as a hero, but as a magical library. Use an atmospheric and slightly melancholic tone in Japanese."}] chat_response = client.chat.completions.create(    model="Local-Novel-LLM-project/Qwen3.5-Hasutsubomi-9B",    messages=messages,    max_tokens=4096,    temperature=0.8, # Slightly higher temperature for creative writing    top_p=0.9,    presence_penalty=1.5,)print("Chat response:", chat_response.choices[0].message.content)

from openai import OpenAI# Configured by environment variablesclient = OpenAI(base_url="http://localhost:8000/v1", api_key="EMPTY") messages =[    {"role": "system", "content": "You are a professional Japanese light novel author."},    {"role": "user", "content": "Write a short prologue for a fantasy Isekai story where the protagonist is reincarnated not as a hero, but as a magical library. Use an atmospheric and slightly melancholic tone in Japanese."}] chat_response = client.chat.completions.create(    model="Local-Novel-LLM-project/Qwen3.5-Hasutsubomi-9B",    messages=messages,    max_tokens=4096,    temperature=0.8, # Slightly higher temperature for creative writing    top_p=0.9,    presence_penalty=1.5,)print("Chat response:", chat_response.choices[0].message.content)

Analyzing Anime/Manga Art (Vision-Language)

python

from openai import OpenAI client = OpenAI(base_url="http://localhost:8000/v1", api_key="EMPTY") messages = [    {        "role": "user",        "content":[            {                "type": "image_url",                "image_url": {                    "url": "https://example.com/anime_character_design.jpg"                }            },            {                "type": "text",                "text": "Analyze this character's design. Based on typical Japanese sub-culture tropes, what kind of personality (e.g., Tsundere, Yandere, Chuunibyou) do they likely have, and what kind of magic would they use in a fantasy setting?"            }        ]    }] chat_response = client.chat.completions.create(    model="Local-Novel-LLM-project/Qwen3.5-Hasutsubomi-9B",    messages=messages,    max_tokens=2048,    temperature=0.7,)print("Chat response:", chat_response.choices[0].message.content)

from openai import OpenAI client = OpenAI(base_url="http://localhost:8000/v1", api_key="EMPTY") messages = [    {        "role": "user",        "content":[            {                "type": "image_url",                "image_url": {                    "url": "https://example.com/anime_character_design.jpg"                }            },            {                "type": "text",                "text": "Analyze this character's design. Based on typical Japanese sub-culture tropes, what kind of personality (e.g., Tsundere, Yandere, Chuunibyou) do they likely have, and what kind of magic would they use in a fantasy setting?"            }        ]    }] chat_response = client.chat.completions.create(    model="Local-Novel-LLM-project/Qwen3.5-Hasutsubomi-9B",    messages=messages,    max_tokens=2048,    temperature=0.7,)print("Chat response:", chat_response.choices[0].message.content)

Best Practices for Hasutsubomi

Prompting for Writing: When asking the model to write stories, it helps to explicitly state the desired trope or genre (e.g., "Cyberpunk", "Isekai", "Slice of Life", "Iyashikei").
Sampling Parameters for Creativity:
- For creative writing and roleplay, we recommend a higher temperature: temperature=0.8 to 1.0 with a top_p=0.9.
- Apply a slight presence_penalty=1.5 to encourage varied vocabulary.
Thinking Mode: Allow the model to utilize <think>\n...\</think> tags to plan out story beats before it generates the final text. This significantly improves narrative coherence.

Citation

If you use this fine-tuned model, please consider acknowledging this repository. Additionally, please cite the original Qwen3.5 paper:

bibtex

@misc{qwen3.5,    title  = {{Qwen3.5}: Towards Native Multimodal Agents},    author = {{Qwen Team}},    month  = {February},    year   = {2026},    url    = {https://qwen.ai/blog?id=qwen3.5}}

@misc{qwen3.5,    title  = {{Qwen3.5}: Towards Native Multimodal Agents},    author = {{Qwen Team}},    month  = {February},    year   = {2026},    url    = {https://qwen.ai/blog?id=qwen3.5}}