Instructions to use Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1")
model = AutoModelForCausalLM.from_pretrained("Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1 with 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 Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1:Q4_K_M

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 Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1:Q4_K_M

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 Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1:Q4_K_M

Use Docker

docker model run hf.co/Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1:Q4_K_M

Llama new
LM Studio
Jan

vLLM

How to use Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1:Q4_K_M

SGLang

How to use Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1 with Ollama:
```
ollama run hf.co/Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1:Q4_K_M
```
Unsloth Desktop

How to use Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1 with Docker Model Runner:
```
docker model run hf.co/Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1:Q4_K_M
```

Lemonade

How to use Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1:Q4_K_M

Run and chat with the model

lemonade run user.Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1 with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1: experimental rank 2048 DoRA finetune of LFM 2.5 2.6B using beyoru/Aesir-Character-CoT-roleplay dataset, pure madness.

"Whoso Pulleth Out This Sword From This Stone and Anvil is Rightwise King Born of England"

The meaning of the experiment:

I wanted to completely reshape the way model thinks, so I took on a little special approach, combining DoRA with ridiculously high rank(2048).

What is DoRA? DoRA is a weight decomposed version of LoRA that achieves higher accuracy at the cost of more training compute, this repo contains merged model, meaning that overhead for the end user is zero.

Here is some horrible photographic evidence:

Final step loss, if anyone is interested, was around 0.95-1~ for this version.

Special thanks:

To Beyoru and Gryphe for the amazing dataset.

And to Unsloth for convenient training.

Note:

Quants are located in the repo.

Training details:

Method: DoRA
Rank: 2048
Training hardware: 5070 ti
Trained for: 5~ hours

Downloads last month: 311

Safetensors

Model size

3B params

Tensor type

BF16

Model tree for Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1

Base model

LiquidAI/LFM2.5-2.6B-Base

Finetuned

LiquidAI/LFM2.5-2.6B

Finetuned

(70)

this model

Quantizations

2 models

Indexnusrefather
/

Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1

Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1: experimental rank 2048 DoRA finetune of LFM 2.5 2.6B using beyoru/Aesir-Character-CoT-roleplay dataset, pure madness.

"Whoso Pulleth Out This Sword From This Stone and Anvil is Rightwise King Born of England"

The meaning of the experiment:

Special thanks:

Note:

Training details:

Model tree for Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1

Dataset used to train Indexnusrefather/Caelistus-Gladius-Excalibur-RP-2.6B-Thinking-v0.1