Text Generation
PEFT
Safetensors
English
qwen3_5_moe_text
lora
qwen3.6
roleplay
creative-writing
interactive-fiction
conversational
4-bit precision
bitsandbytes
Instructions to use Darksp33d/loreweaver-rp-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Darksp33d/loreweaver-rp-v1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("togethercomputer/Qwen3.6-35B-A3B_bnb_4bit_t") model = PeftModel.from_pretrained(base_model, "Darksp33d/loreweaver-rp-v1") - Notebooks
- Google Colab
- Kaggle
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library_name: peft
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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[More Information Needed]
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## Evaluation
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### Testing Data, Factors & Metrics
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#### Testing Data
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[More Information Needed]
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#### Factors
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#### Metrics
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### Results
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#### Summary
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## Model Examination [optional]
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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### Compute Infrastructure
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#### Hardware
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#### Software
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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## Glossary [optional]
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## More Information [optional]
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## Model Card Authors [optional]
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## Model Card Contact
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[More Information Needed]
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### Framework versions
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- PEFT 0.15.1
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base_model: Qwen/Qwen3.6-35B-A3B
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base_model_relation: finetune
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library_name: peft
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pipeline_tag: text-generation
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tags:
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- lora
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- qwen3.6
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- roleplay
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- creative-writing
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- interactive-fiction
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- conversational
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- 4-bit
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- bitsandbytes
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language:
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- en
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# LoreWeaver RP v1
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LoreWeaver RP v1 is a parameter-efficient role-play and interactive-fiction fine-tune of the Qwen3.6-35B-A3B family. It is intended for vivid scene writing, sustained character voice, dialogue, and long-form narrative continuation.
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This repository contains a **LoRA adapter**, not a standalone copy of the base model. A compatible Qwen3.6-35B-A3B base checkpoint is required for inference.
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## Model summary
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| Field | Value |
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| --- | --- |
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| Developer | [Darksp33d](https://huggingface.co/Darksp33d) |
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| Model | [Darksp33d/loreweaver-rp-v1](https://huggingface.co/Darksp33d/loreweaver-rp-v1) |
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| Release date | July 19, 2026 |
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| Task | Autoregressive text generation |
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| Specialization | Role-play, interactive fiction, creative writing, and character dialogue |
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| Model family | Qwen3.6-35B-A3B |
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| Public architectural parent | [Qwen/Qwen3.6-35B-A3B](https://huggingface.co/Qwen/Qwen3.6-35B-A3B) |
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| Adapter format | PEFT LoRA in Safetensors format |
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| Adapter parameters | 13,762,560 |
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| Adapter size | Approximately 55.1 MB |
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| Context declared by tokenizer/config | 262,144 tokens |
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| Primary documented language | English |
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| License | Not yet declared for this adapter; the public Qwen parent is Apache-2.0 |
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The base architecture is a mixture-of-experts model with 40 text layers, 256 experts, and 8 experts selected per token. The public parent contains approximately 35.95B parameters. The adapter repository contains text-model configuration and does not establish that vision behavior was trained, retained, or evaluated; this model card therefore documents LoreWeaver RP v1 as a **text-generation adapter**.
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## Intended uses
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LoreWeaver RP v1 is designed for:
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- interactive story continuation;
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- in-character conversation and dialogue;
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- character-driven role-play;
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- scene narration and descriptive prose;
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- worldbuilding grounded in supplied lore or session context;
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- branching narrative applications in which the user directs the story.
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The model is most useful inside an application that manages character definitions, world lore, memory, recent dialogue, and output constraints. It can also be used directly with a clear system prompt and conversation history.
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### Out-of-scope uses
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This adapter was not developed or evaluated for:
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- factual question answering or retrieval;
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- medical, legal, financial, or other high-stakes decisions;
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- autonomous real-world actions;
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- identity verification or claims about real people;
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- code generation;
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- image, audio, or video understanding;
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- guaranteed policy enforcement or content moderation.
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Do not treat generated narrative as factual, and do not use the model to impersonate a real person without their consent.
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## Prompt format
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Use the tokenizer and chat template shipped with the adapter repository. The template accepts `system`, `user`, `assistant`, and `tool` roles.
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LoreWeaver RP v1 is intended to return finished narrative output rather than visible reasoning. For runtimes that support the included template arguments, set:
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```python
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enable_thinking=False
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```
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A minimal conversation looks like:
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```python
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messages = [
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{
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"role": "system",
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"content": (
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"Write immersive interactive fiction. Maintain character voice, "
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"respect established lore, and never decide the player's actions."
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),
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},
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{
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"role": "user",
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"content": "I push open the observatory door and call for Mara.",
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},
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