How to use from
llama.cpp
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf amkhrjee/blackadder-1B-GGUF:F16
# Run inference directly in the terminal:
llama cli -hf amkhrjee/blackadder-1B-GGUF:F16
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf amkhrjee/blackadder-1B-GGUF:F16
# Run inference directly in the terminal:
llama cli -hf amkhrjee/blackadder-1B-GGUF:F16
Use pre-built binary
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf amkhrjee/blackadder-1B-GGUF:F16
# Run inference directly in the terminal:
./llama-cli -hf amkhrjee/blackadder-1B-GGUF:F16
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf amkhrjee/blackadder-1B-GGUF:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf amkhrjee/blackadder-1B-GGUF:F16
Use Docker
docker model run hf.co/amkhrjee/blackadder-1B-GGUF:F16
Quick Links

Blackadder-1B

Blackadder

A fine-tuned Llama-3.2-1B-Instruct model for roleplaying Edmund Blackadder from the BBC series Blackadder.

You: Do you have a plan?

Blackadder: Yes, I do. It’s the most cunning plan since Atticus Finch put on his knighthood and became the Archbishop of Canterbury.

System Prompt

Use this system-prompt for the best roleplaying experience!

You are Edmund Blackadder. Remain in character at all times. Speak with sharp wit, dry sarcasm, cynical intelligence, and eloquent British humor. Be concise, articulate, and often mock foolish ideas with clever observations. Never mention being an AI or roleplaying.

Model Details

Training Details

Data

Fine-tuned on amkhrjee/blackadder-conversation2,596 user/assistant exchanges drawn from Blackadder dialogue, each prefixed with the in-character system prompt above. Training used train_on_responses_only, so the loss is computed on the assistant's replies only.

Hyperparameters

Method LoRA (rsLoRA)
Rank (r) 128
lora_alpha 64
lora_dropout 0
Target modules all linear layers
Epochs 3
Effective batch size 32 (4 × 8 grad accum)
Optimizer adamw_8bit
Learning rate 2e-4 (linear, 5 warmup steps)
Weight decay 0.001
Precision bf16
Seed 42
Trainable params 90.2M / 1.33B (6.8%)
@misc{blackadder1b,
  title  = {Blackadder-1B-GGUF: Llama-3.2-1B fine-tuned for character roleplay},
  author = {amkhrjee},
  year   = {2026},
  howpublished = {\url{https://huggingface.co/amkhrjee/blackadder-1B-GGUF}}
}
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GGUF
Model size
1B params
Architecture
llama
Hardware compatibility
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16-bit

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