Instructions to use rlucasfm/qwen2.5-eqtlab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use rlucasfm/qwen2.5-eqtlab with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="rlucasfm/qwen2.5-eqtlab",
	filename="unsloth.F16.gguf",
)

llm.create_chat_completion(
	messages = "{\n    \"question\": \"What is my name?\",\n    \"context\": \"My name is Clara and I live in Berkeley.\"\n}"
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use rlucasfm/qwen2.5-eqtlab with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf rlucasfm/qwen2.5-eqtlab:F16
# Run inference directly in the terminal:
llama-cli -hf rlucasfm/qwen2.5-eqtlab:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf rlucasfm/qwen2.5-eqtlab:F16
# Run inference directly in the terminal:
llama-cli -hf rlucasfm/qwen2.5-eqtlab: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 rlucasfm/qwen2.5-eqtlab:F16
# Run inference directly in the terminal:
./llama-cli -hf rlucasfm/qwen2.5-eqtlab: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 rlucasfm/qwen2.5-eqtlab:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf rlucasfm/qwen2.5-eqtlab:F16

Use Docker

docker model run hf.co/rlucasfm/qwen2.5-eqtlab:F16

LM Studio
Jan
Ollama
How to use rlucasfm/qwen2.5-eqtlab with Ollama:
```
ollama run hf.co/rlucasfm/qwen2.5-eqtlab:F16
```

Unsloth Studio

How to use rlucasfm/qwen2.5-eqtlab 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 rlucasfm/qwen2.5-eqtlab 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 rlucasfm/qwen2.5-eqtlab to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for rlucasfm/qwen2.5-eqtlab to start chatting

How to use rlucasfm/qwen2.5-eqtlab with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf rlucasfm/qwen2.5-eqtlab:F16

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": "rlucasfm/qwen2.5-eqtlab:F16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use rlucasfm/qwen2.5-eqtlab with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf rlucasfm/qwen2.5-eqtlab:F16

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 rlucasfm/qwen2.5-eqtlab:F16

Run Hermes

hermes

Atomic Chat new
Docker Model Runner
How to use rlucasfm/qwen2.5-eqtlab with Docker Model Runner:
```
docker model run hf.co/rlucasfm/qwen2.5-eqtlab:F16
```

Lemonade

How to use rlucasfm/qwen2.5-eqtlab with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull rlucasfm/qwen2.5-eqtlab:F16

Run and chat with the model

lemonade run user.qwen2.5-eqtlab-F16

List all available models

lemonade list

Model Card for Model ID

Modelo feito por fine-tuning do Qwen 2.5 1.5B para responder conteúdos relacionados ao EQT Lab. Dataset de treinamento sintético criado a partir de conteúdos disponíveis online no site do EQT Lab. Modelo slim para inferência em ambiente local

Model Details

Model Description

Developed by: Richard Lucas F. de Mendonça - EQT Lab
Model type: Chat LLM
Language(s) (NLP): Portuguesse
Finetuned from model: Qwen 2.5 1.5B Instruct from Unsloth

Uses

Este modelo foi criado com o objetivo de ser usado como um "guia local" para o EQT Lab, rodando on-premisses.

Direct Use

Este modelo será usado diretamente para inferência em chat no servidor local. Deve ser usado apenas como modelo conversacional interno da EQT Lab.

Out-of-Scope Use

[More Information Needed]

Bias, Risks, and Limitations

[More Information Needed]

Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

Use the code below to get started with the model.

[More Information Needed]

Training Details

Training Data

[More Information Needed]

Training Procedure

Downloads last month: 9

GGUF

Model size

2B params

Architecture

qwen2

Hardware compatibility

4-bit

16-bit

Model tree for rlucasfm/qwen2.5-eqtlab

Base model

Qwen/Qwen2.5-1.5B

Finetuned

Qwen/Qwen2.5-1.5B-Instruct

Finetuned

unsloth/Qwen2.5-1.5B-Instruct

Quantized

(12)

this model