Text Generation
MLX
Safetensors
English
Italian
llama
conversational
sft
children
storytelling
italian
english
Instructions to use giux78/buddy-nesso-sft-v1-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use giux78/buddy-nesso-sft-v1-mlx with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("giux78/buddy-nesso-sft-v1-mlx") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use giux78/buddy-nesso-sft-v1-mlx with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "giux78/buddy-nesso-sft-v1-mlx"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "giux78/buddy-nesso-sft-v1-mlx" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "giux78/buddy-nesso-sft-v1-mlx", "messages": [ {"role": "user", "content": "Hello"} ] }'
Buddy Nesso SFT v1 โ MLX
MLX conversion (bfloat16) of giux78/buddy-nesso-sft-v1, a 0.4B parameter bilingual (Italian/English) story and play buddy for children under 8, fine-tuned from mii-llm/nesso-0.4B-agentic.
Converted with mlx-lm for fast local inference on Apple Silicon. See the base model card for training details, the recommended child-safety system prompt, and important safety limitations โ this is a research checkpoint, not a production child-safety model.
Usage
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("giux78/buddy-nesso-sft-v1-mlx")
messages = [
{"role": "system", "content": "You are Nesso, a warm story and play buddy for children under 8. Keep replies short and safe."},
{"role": "user", "content": "Ciao! Mi racconti una storia di un piccolo orso?"},
]
prompt = tokenizer.apply_chat_template(messages, add_generation_prompt=True, tokenize=False)
print(generate(model, tokenizer, prompt=prompt, max_tokens=150))
Or from the command line:
mlx_lm.chat --model giux78/buddy-nesso-sft-v1-mlx
Voice demo
A complete voice-interactive demo (speech in โ Nesso โ speech out, fully local on a Mac) is available at mii-llm/buddy-nesso-voice-demo.
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Model size
0.4B params
Tensor type
BF16
ยท
Hardware compatibility
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Quantized
Model tree for giux78/buddy-nesso-sft-v1-mlx
Base model
mii-llm/zagreus-0.4B-ita Finetuned
mii-llm/nesso-0.4B-agentic Finetuned
giux78/buddy-nesso-sft-v1