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, with persona set 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 16 when serving)
  • Trained for this personaโ€™s 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.

Downloads last month
387
GGUF
Model size
65M params
Architecture
gemma4
Hardware compatibility
Log In to add your hardware

16-bit

Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐Ÿ™‹ Ask for provider support