Libraries MLX How to use versae/filiberto-7B-instruct-exp1 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("versae/filiberto-7B-instruct-exp1")
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) llama-cpp-python How to use versae/filiberto-7B-instruct-exp1 with llama-cpp-python:
# !pip install llama-cpp-python
from llama_cpp import Llama
llm = Llama.from_pretrained(
repo_id="versae/filiberto-7B-instruct-exp1",
filename="ggml-model-f16.gguf",
)
llm.create_chat_completion(
messages = [
{
"role": "user",
"content": "What is the capital of France?"
}
]
) Notebooks Google Colab Kaggle Local Apps Settings llama.cpp How to use versae/filiberto-7B-instruct-exp1 with llama.cpp:
Install from brew brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf versae/filiberto-7B-instruct-exp1:F16
# Run inference directly in the terminal:
llama-cli -hf versae/filiberto-7B-instruct-exp1:F16 Install from WinGet (Windows) winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf versae/filiberto-7B-instruct-exp1:F16
# Run inference directly in the terminal:
llama-cli -hf versae/filiberto-7B-instruct-exp1: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 versae/filiberto-7B-instruct-exp1:F16
# Run inference directly in the terminal:
./llama-cli -hf versae/filiberto-7B-instruct-exp1: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 versae/filiberto-7B-instruct-exp1:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf versae/filiberto-7B-instruct-exp1:F16 Use Docker docker model run hf.co/versae/filiberto-7B-instruct-exp1:F16 LM Studio Jan vLLM How to use versae/filiberto-7B-instruct-exp1 with vLLM:
Install from pip and serve model # Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "versae/filiberto-7B-instruct-exp1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "versae/filiberto-7B-instruct-exp1",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}' Use Docker docker model run hf.co/versae/filiberto-7B-instruct-exp1:F16 Ollama How to use versae/filiberto-7B-instruct-exp1 with Ollama:
ollama run hf.co/versae/filiberto-7B-instruct-exp1:F16 Unsloth Studio How to use versae/filiberto-7B-instruct-exp1 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 versae/filiberto-7B-instruct-exp1 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 versae/filiberto-7B-instruct-exp1 to start chatting Using HuggingFace Spaces for Unsloth # No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for versae/filiberto-7B-instruct-exp1 to start chatting MLX LM How to use versae/filiberto-7B-instruct-exp1 with MLX LM:
Generate or start a chat session # Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "versae/filiberto-7B-instruct-exp1" Run an OpenAI-compatible server # Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "versae/filiberto-7B-instruct-exp1"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "versae/filiberto-7B-instruct-exp1",
"messages": [
{"role": "user", "content": "Hello"}
]
}' Docker Model Runner How to use versae/filiberto-7B-instruct-exp1 with Docker Model Runner:
docker model run hf.co/versae/filiberto-7B-instruct-exp1:F16 Lemonade How to use versae/filiberto-7B-instruct-exp1 with Lemonade:
Pull the model # Download Lemonade from https://lemonade-server.ai/
lemonade pull versae/filiberto-7B-instruct-exp1:F16 Run and chat with the model lemonade run user.filiberto-7B-instruct-exp1-F16 List all available models lemonade list 
