Instructions to use Inserloft/NaNo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Inserloft/NaNo with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Inserloft/NaNo",
	filename="NaNo-V3.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use Inserloft/NaNo with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Inserloft/NaNo
# Run inference directly in the terminal:
llama-cli -hf Inserloft/NaNo

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Inserloft/NaNo
# Run inference directly in the terminal:
llama-cli -hf Inserloft/NaNo

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 Inserloft/NaNo
# Run inference directly in the terminal:
./llama-cli -hf Inserloft/NaNo

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 Inserloft/NaNo
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Inserloft/NaNo

Use Docker

docker model run hf.co/Inserloft/NaNo

LM Studio
Jan
Ollama
How to use Inserloft/NaNo with Ollama:
```
ollama run hf.co/Inserloft/NaNo
```

Unsloth Studio new

How to use Inserloft/NaNo 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 Inserloft/NaNo 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 Inserloft/NaNo to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Inserloft/NaNo to start chatting

Docker Model Runner
How to use Inserloft/NaNo with Docker Model Runner:
```
docker model run hf.co/Inserloft/NaNo
```

Lemonade

How to use Inserloft/NaNo with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Inserloft/NaNo

Run and chat with the model

lemonade run user.NaNo-{{QUANT_TAG}}

List all available models

lemonade list

NaNo / README.md

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	---
	language:
	- es
	- en
	license: mit
	tags:
	- gpt2
	- code
	- bilingual
	- inserloft
	model_name: Cleo Nano v3.1 Bilingual
	---

	# Cleo Nano v3.1 (Bilingual Optimization)

	Cleo Nano is a decoder-only Transformer model developed by Inserloft under the vision of Jesus Heriberto Corona. This version (v3.1) features surgical fine-tuning for bilingual stability (English/Spanish) and hallucination control.

	## Model Details
	- Architecture: Decoder-Only GPT (Custom)
	- Layers: 8
	- Embedding Dim: 384
	- Attention Heads: 12
	- Context Window: 256 tokens
	- Parameters: ~15M
	- Training Data: Mix of Wikipedia, Python Code (CodeFeedback), and Identity Anchoring.

	## Usage
	To use this model, you need the custom `CleoNanoV3` architecture defined in PyTorch. The weights can be loaded using `torch.load()` or via the Hugging Face `from_pretrained` if using the provided mapping logic.

	### Capabilities
	1. Bilingual Chat: Responds to general queries in both Spanish and English.
	2. Code Generation: Specialized in Python snippets (Sum, Loops, Classes).
	3. Identity Preservation: Strong grounding on its origin and creator.

	---
	Developed by [Inserloft](https://inserloft.dev/)