Instructions to use burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF", dtype="auto") - llama-cpp-python
How to use burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF", filename="bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF.Q4_K_M.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF: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 burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF: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 burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF:Q4_K_M
Use Docker
docker model run hf.co/burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF with Ollama:
ollama run hf.co/burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF:Q4_K_M
- Unsloth Studio
How to use burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF 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 burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF 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 burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF to start chatting
- Pi
How to use burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF: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": "burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF: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 burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat new
- Docker Model Runner
How to use burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF with Docker Model Runner:
docker model run hf.co/burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF:Q4_K_M
- Lemonade
How to use burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull burgasdotpro/bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.bgGPT-GRPO-Llama-3.1-8B-Inst-GGUF-Q4_K_M
List all available models
lemonade list
Мислеща модела базирана на llama-3.1-8b-instruct
Не е deepseek, а стандартна модела научена да мисли.
Актуализиран 15.02.2025
- Changed training params
- GRPO
- Бъългарски токени
Релиз: 14.02.2025
- GRPO
Пример:
SYSTEM:"""
Отговори в следния формат:
<мислене>
...
</мислене>
<отговор>
...
</отговор>
"""
USER: Колко е 2 + 2?
ASSISTANT:
<мислене>
2 + 2 е едно от най-елементарните аритметични операции.
При изпълнението на тази операция се позволява да се запишат
числата в еднакви групи и се даде обща им стойност.
Има два брояча в групите, които запълват всеки един с две единици.
След това се сумира стойността на двете групи, което води до 2 + 2 = 4.
</мислене>
<отговор>
4
</отговор>
Uploaded model
- Developed by: burgasdotpro
- License: apache-2.0
- Finetuned from model : unsloth/meta-llama-3.1-8b-instruct-bnb-4bit
Тази llama модела тренирана 2 пъти по-бързо с помоща на Unsloth и TRL библиотеката на Huggingface.
- Downloads last month
- 45
4-bit
5-bit
6-bit
8-bit
