Instructions to use bartowski/LLaMA3-iterative-DPO-final-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use bartowski/LLaMA3-iterative-DPO-final-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="bartowski/LLaMA3-iterative-DPO-final-GGUF", filename="LLaMA3-iterative-DPO-final-IQ1_M.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use bartowski/LLaMA3-iterative-DPO-final-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf bartowski/LLaMA3-iterative-DPO-final-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf bartowski/LLaMA3-iterative-DPO-final-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 bartowski/LLaMA3-iterative-DPO-final-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf bartowski/LLaMA3-iterative-DPO-final-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 bartowski/LLaMA3-iterative-DPO-final-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf bartowski/LLaMA3-iterative-DPO-final-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 bartowski/LLaMA3-iterative-DPO-final-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf bartowski/LLaMA3-iterative-DPO-final-GGUF:Q4_K_M
Use Docker
docker model run hf.co/bartowski/LLaMA3-iterative-DPO-final-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use bartowski/LLaMA3-iterative-DPO-final-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bartowski/LLaMA3-iterative-DPO-final-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bartowski/LLaMA3-iterative-DPO-final-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/bartowski/LLaMA3-iterative-DPO-final-GGUF:Q4_K_M
- Ollama
How to use bartowski/LLaMA3-iterative-DPO-final-GGUF with Ollama:
ollama run hf.co/bartowski/LLaMA3-iterative-DPO-final-GGUF:Q4_K_M
- Unsloth Studio new
How to use bartowski/LLaMA3-iterative-DPO-final-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 bartowski/LLaMA3-iterative-DPO-final-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 bartowski/LLaMA3-iterative-DPO-final-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for bartowski/LLaMA3-iterative-DPO-final-GGUF to start chatting
- Docker Model Runner
How to use bartowski/LLaMA3-iterative-DPO-final-GGUF with Docker Model Runner:
docker model run hf.co/bartowski/LLaMA3-iterative-DPO-final-GGUF:Q4_K_M
- Lemonade
How to use bartowski/LLaMA3-iterative-DPO-final-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull bartowski/LLaMA3-iterative-DPO-final-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.LLaMA3-iterative-DPO-final-GGUF-Q4_K_M
List all available models
lemonade list
This model has the same metadata problem as the BPE fix model
Sorry for bringing this up again here, but this model is showing as 7B in LM Studio
Here is the metadata
{
"name": "SFR-Iterative-DPO-LLaMA-3-8B-R",
"arch": "llama",
"quant": "Q8_0",
"context_length": 8192,
"embedding_length": 4096,
"num_layers": 32,
"rope": {
"freq_base": 500000,
"dimension_count": 128
},
"head_count": 32,
"head_count_kv": 8,
"parameters": "7B"
}
Hey @yehiaserag no problem !
Yeah not sure why it's doing that, I'm not editing the metadata or anything.. do you know by chance if all other 8B models have this issue?
This metadata is coming from where, lmstudio or the actual GGUF metadata? Where do you see these values?
The original first gguf that had the tokenizer problem was showing as 8B.
Llama.cpp repo has a python script that edits this metadata, but if you are not explicitly setting it to 7B, maybe be it's quessed/infered in the quantization process somewhere...