Instructions to use LazyLoopStudio/Nomi-1-Creative with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use LazyLoopStudio/Nomi-1-Creative with Adapters:

from adapters import AutoAdapterModel

model = AutoAdapterModel.from_pretrained("undefined")
model.load_adapter("LazyLoopStudio/Nomi-1-Creative", set_active=True)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use LazyLoopStudio/Nomi-1-Creative 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 LazyLoopStudio/Nomi-1-Creative:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf LazyLoopStudio/Nomi-1-Creative:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf LazyLoopStudio/Nomi-1-Creative:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf LazyLoopStudio/Nomi-1-Creative: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 LazyLoopStudio/Nomi-1-Creative:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf LazyLoopStudio/Nomi-1-Creative: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 LazyLoopStudio/Nomi-1-Creative:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf LazyLoopStudio/Nomi-1-Creative:Q4_K_M

Use Docker

docker model run hf.co/LazyLoopStudio/Nomi-1-Creative:Q4_K_M

LM Studio
Jan

vLLM

How to use LazyLoopStudio/Nomi-1-Creative with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/LazyLoopStudio/Nomi-1-Creative:Q4_K_M

Ollama
How to use LazyLoopStudio/Nomi-1-Creative with Ollama:
```
ollama run hf.co/LazyLoopStudio/Nomi-1-Creative:Q4_K_M
```

Unsloth Studio

How to use LazyLoopStudio/Nomi-1-Creative with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for LazyLoopStudio/Nomi-1-Creative to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for LazyLoopStudio/Nomi-1-Creative to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for LazyLoopStudio/Nomi-1-Creative to start chatting

How to use LazyLoopStudio/Nomi-1-Creative with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf LazyLoopStudio/Nomi-1-Creative:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "LazyLoopStudio/Nomi-1-Creative:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use LazyLoopStudio/Nomi-1-Creative with Docker Model Runner:
```
docker model run hf.co/LazyLoopStudio/Nomi-1-Creative:Q4_K_M
```

Lemonade

How to use LazyLoopStudio/Nomi-1-Creative with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull LazyLoopStudio/Nomi-1-Creative:Q4_K_M

Run and chat with the model

lemonade run user.Nomi-1-Creative-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use LazyLoopStudio/Nomi-1-Creative with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf LazyLoopStudio/Nomi-1-Creative: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 LazyLoopStudio/Nomi-1-Creative:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use LazyLoopStudio/Nomi-1-Creative with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf LazyLoopStudio/Nomi-1-Creative: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 "LazyLoopStudio/Nomi-1-Creative: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"

Schnuckade commited on Feb 11

Commit

ccbf0ac

verified ·

1 Parent(s): cae6aed

Add README

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README.md +14 -62

README.md CHANGED Viewed

@@ -1,71 +1,23 @@
 ---
-license: apache-2.0
-base_model: unsloth/Qwen2.5-3B-Instruct-bnb-4bit
-language:
-- en
-- de
 tags:
-- creative
-- flash
-- roleplay
 - unsloth
-- lazyloopstudio
-- nomi
-- creative_writing
-- nomi flash
-- nomi 1
-model_name: Nomi-1-Flash
-datasets:
-- databricks/databricks-dolly-15k
-metrics:
-- character
-pipeline_tag: text-generation
-library_name: transformers
----
-<div align="center">
-![Znomi_nbg](https://cdn-uploads.huggingface.co/production/uploads/6921fa6332f7fb129563d495/9oOMYWNoxBDmF854MciTn.png)
-</div>
-# Nomi-1-Flash ⚡
-**Nomi-1-Flash** is a high-speed, creative-focused AI companion based on the Qwen 2.5 3B architecture. Developed by **LazyLoopStudio**, this model is fine-tuned to prioritize vibrant personality, creative vocabulary, and rapid responses over rigid technical instruction following.
-## 📊 Evaluation & Benchmarks
-We believe in transparency. Nomi-1-Flash was tested using a custom evaluation suite to measure its "Creative First" approach.
-| Metric | Score | Interpretation |
-| :--- | :---: | :--- |
-| **Creativity Index** | **100.0%** | Exceptional vocabulary diversity and imaginative flair. |
-| **General Knowledge (MMLU)** | **48.0%** | Solid factual foundation, comparable to mid-sized models. |
-| **Instruction Following (IFEval)** | **33.3%** | Low. Nomi tends to prioritize style over strict formatting rules. |
-### Summary
-Nomi-1-Flash is **not** a coding or logic expert. She is a storyteller and a conversationalist. While her instruction following is lower than the base model, her creative output is significantly more engaging and human-like.
-## 🚀 Quick Start (Inference)
-To use Nomi-1-Flash in Python (requires `unsloth` or `transformers`):
-```python
-from unsloth import FastLanguageModel
-import torch
-model, tokenizer = FastLanguageModel.from_pretrained(
-    model_name = "LazyLoopStudio/Nomi-1-Flash",
-    max_seq_length = 2048,
-    load_in_4bit = True,
-)
-FastLanguageModel.for_inference(model)
-prompt = "Write a creative opening for a story about a neon-lit cloud city."
-inputs = tokenizer([f"<|im_start|>user\n{prompt}<|im_end|>\n<|im_start|>assistant\n"], return_tensors="pt").to("cuda")
-outputs = model.generate(**inputs, max_new_tokens=256)
-print(tokenizer.batch_decode(outputs)[0])

 ---
 tags:
+- gguf
+- llama.cpp
 - unsloth
+---
+# Nomi-1-Flash : GGUF
+This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
+**Example usage**:
+- For text only LLMs:    `./llama.cpp/llama-cli -hf LazyLoopStudio/Nomi-1-Flash --jinja`
+- For multimodal models: `./llama.cpp/llama-mtmd-cli -hf LazyLoopStudio/Nomi-1-Flash --jinja`
+## Available Model files:
+- `Qwen2.5-3B-Instruct.Q8_0.gguf`
+## Ollama
+An Ollama Modelfile is included for easy deployment.
+This was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth)
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)