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README.md
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---
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license: mit
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base_model: Qwen/Qwen3-14B-Base
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tags:
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- cpt
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- continued-pretraining
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- roleplay
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- creative-writing
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- character-cards
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- fiction
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datasets:
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- nyuuzyou/fandom
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- gryffindor-ISWS/dbpedia_abstracts_fictional_characters_with_img
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language:
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- en
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pipeline_tag: text-generation
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---
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# SpoomplesMaxx Base
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A continued pre-training (CPT) checkpoint of [Qwen/Qwen3-14B-Base](https://huggingface.co/Qwen/Qwen3-14B-Base) fine-tuned on creative writing and roleplay data.
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## Model Description
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This model is part of the SpoomplesMaxx training pipeline: **CPT → SFT → DPO**
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The CPT stage teaches the model:
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- Character understanding and portrayal
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- Creative fiction writing patterns
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- Fandom/wiki-style lore knowledge
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- Dialogue patterns for roleplay
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## Training Data
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### Phase 1: Core Knowledge
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This checkpoint was trained on data focused on character knowledge and lore:
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| Dataset | Source | Samples | Description |
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|---------|--------|---------|-------------|
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| **Private Dataset** | Private | ~100k (50,000 sampled) | SillyTavern-style character cards with personality, scenario, and example dialogue, as well as fanfics, essays about media and characters, short novels, and high quality roleplay data |
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| [nyuuzyou/fandom](https://huggingface.co/datasets/nyuuzyou/fandom) | HuggingFace | 50,000 (sampled) | Fandom wiki articles with character/world lore |
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| [gryffindor-ISWS/dbpedia_abstracts_fictional_characters_with_img](https://huggingface.co/datasets/gryffindor-ISWS/dbpedia_abstracts_fictional_characters_with_img) | HuggingFace | 50,000 (sampled) | DBpedia abstracts of fictional characters |
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**Total training samples:** ~46k
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## Training Configuration
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| Parameter | Value |
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|-----------|-------|
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| Base Model | `Qwen/Qwen3-14B-Base` |
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| Training Phase | Phase 1 (Core Knowledge) |
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| Steps | 1000 / 3000 |
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| Batch Size | 1 |
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| Gradient Accumulation | 16 |
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| **Effective Batch Size** | **16** |
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| Learning Rate | 1e-5 |
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| LR Scheduler | Cosine |
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| Warmup Ratio | 5% |
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| Max Sequence Length | 8192 |
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| Precision | BF16 |
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| Optimizer | 8-bit Paged AdamW |
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| Gradient Checkpointing | ✓ |
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| Priority Repeat | 50× (character cards) |
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### Hardware
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- **GPU:** 1× NVIDIA A800
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- **Training Time:** ~6 hours for 1000 steps
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## Intended Use
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This model is intended for use as a creative base model for further finetuning.
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### Not Recommended For:
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- Production deployment (use final model after full CPT → SFT → DPO pipeline)
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- Direct chat/instruction following (this is a base model continuation, not instruction-tuned)
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## Limitations
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- **No instruction tuning:** This model continues raw text, not chat/instructions
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- **Private data bias:** Heavy weighting toward private character cards may introduce specific character patterns
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- **NSFW content:** Training data includes creative fiction that may contain mature themes. No safety filtering was applied at this stage.
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## How to Use
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained(
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"aimeri/SpoomplesMaxx-CPT-3-Base",
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dtype="auto",
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device_map="auto",
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)
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tokenizer = AutoTokenizer.from_pretrained("aimeri/SpoomplesMaxx-CPT-3-Base")
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# CPT models continue text, not chat
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prompt = "The castle stood silent against the darkening sky, its towers reaching toward clouds that promised rain. Inside,"
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inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
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outputs = model.generate(**inputs, max_new_tokens=200, do_sample=True, temperature=0.8)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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## Citation
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If you use this model, please cite the base model and datasets:
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```bibtex
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@misc{qwen3-14b-base,
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title={Qwen3-14B-Base},
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author={Qwen Team},
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year={2025},
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publisher={Hugging Face},
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url={https://huggingface.co/Qwen/Qwen3-14B-Base}
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}
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```
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## Acknowledgments
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- [Qwen Team](https://huggingface.co/Qwen) for the excellent base model
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- [nyuuzyou](https://huggingface.co/nyuuzyou) for the Fandom wiki dataset
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- [Archive of Our Own](https://archiveofourown.org/) for creative fiction
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---
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