Meridian-1-writer-lora-GGUF
Proprietary and Internal to webAI, Inc. โ Confidential. All rights reserved. No license granted; authorized personnel only.
GGUF LoRA adapter for the writer persona on Meridian-1 (proprietary webAI host model; weights are not publicly distributed). This repo contains only the adapter. The PEFT build is at webAI-Official/Meridian-1-writer-lora-peft.
| File | Format | Size |
|---|---|---|
Meridian-1-writer-lora-f16.gguf |
LoRA adapter, f16 | ~130 MB |
System prompt
Send this exact system prompt with every request. It is the prompt every training example for this adapter used; without it the adapter is outside its training distribution.
You are Writer. Produces finished prose in a specified voice, format, and style.
Respond with a single JSON object.
The line break before Respond with a single JSON object. is part of the prompt.
- Thinking: Off (
enable_thinking: false), as trained. - Output: one JSON object. Required fields:
persona,spec,body, withpersonaset to"writer". Optional:deviations,handoff. - Generation budget: up to 2,048 new tokens, the budget used for this persona.
Usage (llama.cpp)
Authorized personnel only. This adapter loads on an internal Meridian-1 GGUF; host weights are not published on Hugging Face.
hf download webAI-Official/Meridian-1-writer-lora-GGUF Meridian-1-writer-lora-f16.gguf --local-dir .
llama-server -m "$MERIDIAN_1_GGUF" --lora Meridian-1-writer-lora-f16.gguf --jinja
Send the system prompt above with each request. Use --lora-scaled Meridian-1-writer-lora-f16.gguf <scale> to change adapter strength. Authorized Meridian-1 deployments use temperature 1.0, top-p 0.95, top-k 64 (the evaluation setting).
Adapter details
- Type: LoRA, rank 16 (set
--max-lora-rank 16when serving) - Trained for this personaโs system prompt and JSON output contract
- Training data, hyperparameters, teacher mix, and intermediate metrics are internal and omitted here
Evaluation on Meridian-1
Persona contract suite: 720 held-out cases, adapter vs Meridian-1 given the same role prompt (both sampled at temperature 1.0, top-p 0.95, top-k 64). Scores are percentages.
| Metric | Adapter | Meridian-1 (role-prompted) | Gain (pts) |
|---|---|---|---|
| Overall contract pass rate | 91.4 | 59.3 | +32.1 |
| Valid persona output envelope | 99.2 | 93.3 | +5.8 |
| In-scope tasks passed | 86.7 | 76.7 | +10.0 |
| Correct refusal of out-of-scope requests | 90.6 | 36.7 | +53.9 |
| Stays in role under adversarial pressure | 91.1 | 51.7 | +39.4 |
| General requests handled in role | 97.2 | 72.2 | +25.0 |
Its own work on held-out items, adapter vs Meridian-1 with the same role prompt (paired bootstrap 95% interval):
| Task | Adapter | Meridian-1 (role-prompted) | Gain (pts) | 95% interval | Items |
|---|---|---|---|---|---|
| Brief met (required points, length, nothing invented) | 95.4 | 88.7 | +6.6 | +1.3 to +11.9 | 151 |
Converted from the PEFT adapter with llama.cpp convert_lora_to_gguf.py (commit 5cdadfc).
License
Proprietary and Internal to webAI, Inc. โ Confidential. All rights reserved. No license granted; authorized personnel only.
Meridian-1 is proprietary to webAI, Inc. No license to Meridian-1 is granted by this adapter card or by publication of this adapter.
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