Downloads · 30 days
9
2% of all-time downloads
issdandavis/polly-scbe-7b-v2-merged
polly-scbe-7b-v2-merged is a text generation model from issdandavis. Use it when you need the model to write or continue text. The card lists the license as apache-2.0.
Status: canonical. Current Polly release. Merged full-weight build; LoRA adapter at polly-scbe-7b-v2. Other polly- repos are earlier experiments and are tagged superseded.
Downloads · 30 days
9
2% of all-time downloads
All-time downloads
451
Public
Parameters
7.6B
7.7 GB on disk
Likes
0
Public
Click a slice to open those files.
.safetensors7.7 GB · 100%
How the weights are stored.
U86.5B · 86%
From the Hugging Face model README
Status: canonical. Current Polly release. Merged full-weight build; LoRA adapter at polly-scbe-7b-v2. Other
polly-*repos are earlier experiments and are taggedsuperseded.
Polly is a conversational + governance-aware language model fine-tuned on the SCBE-AETHERMOORE framework. Named after a raven familiar from 528 pages of Everweave RPG lore — the same corpus that seeded the Sacred Tongues tokenizer.
This is the merged (full-weight) version. LoRA adapter at issdandavis/polly-scbe-7b-v2.
SCBE-AETHERMOORE is a 14-layer AI safety pipeline using hyperbolic geometry (Poincare ball model). The Sacred Tongues tokenizer encodes text through 6 language-archetype dimensions:
| Code | Tongue | Spirit | Role |
|---|---|---|---|
| KO | Kor'aelin | Python / precise | User intent |
| AV | Avali | JS / reactive | System context |
| RU | Runethic | Rust / ethical | Structural reasoning |
| CA | Cassisivadan | Mathematica / symbolic | Model output |
| UM | Umbroth | Haskell / pure-functional | Deep abstraction |
| DR | Draumric | Markdown / narrative | Integrity seal |
Unlike standard tokenizers built from frequency statistics, Sacred Tongues was seeded from 528 pages of collaborative RPG world-building — giving the vocabulary semantic density from character arcs, dimensional magic, and governance rituals rather than raw token frequency.
The tokenizer routes each conversation role through its canonical tongue:
system → Avali (header context)user → Kor'aelin (intent)assistant → Cassisivadan (output)tool → Draumric (integrity)from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained(
"issdandavis/polly-scbe-7b-v2-merged",
device_map="auto",
load_in_4bit=True,
)
tokenizer = AutoTokenizer.from_pretrained("issdandavis/polly-scbe-7b-v2-merged")
messages = [{"role": "user", "content": "Explain the SCBE governance pipeline."}]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(text, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
| Model | Base | Notes |
|---|---|---|
| polly-scbe-7b-v2 | Qwen2.5-7B | LoRA adapter (this run) |
| polly-prime-r7-qwen-1.5b | Qwen2.5-Coder-1.5B | r7 coder fine-tune |
| polly-r8-qwen-0.5b | Qwen2.5-Coder-0.5B | r8 Kaggle run |