Instructions to use bartowski/Phi-3-medium-4k-instruct-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use bartowski/Phi-3-medium-4k-instruct-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf bartowski/Phi-3-medium-4k-instruct-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf bartowski/Phi-3-medium-4k-instruct-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf bartowski/Phi-3-medium-4k-instruct-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf bartowski/Phi-3-medium-4k-instruct-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/Phi-3-medium-4k-instruct-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf bartowski/Phi-3-medium-4k-instruct-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/Phi-3-medium-4k-instruct-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf bartowski/Phi-3-medium-4k-instruct-GGUF:Q4_K_M
Use Docker
docker model run hf.co/bartowski/Phi-3-medium-4k-instruct-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use bartowski/Phi-3-medium-4k-instruct-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bartowski/Phi-3-medium-4k-instruct-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/Phi-3-medium-4k-instruct-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/bartowski/Phi-3-medium-4k-instruct-GGUF:Q4_K_M
- Ollama
How to use bartowski/Phi-3-medium-4k-instruct-GGUF with Ollama:
ollama run hf.co/bartowski/Phi-3-medium-4k-instruct-GGUF:Q4_K_M
- Unsloth Studio
How to use bartowski/Phi-3-medium-4k-instruct-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/Phi-3-medium-4k-instruct-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/Phi-3-medium-4k-instruct-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/Phi-3-medium-4k-instruct-GGUF to start chatting
- Docker Model Runner
How to use bartowski/Phi-3-medium-4k-instruct-GGUF with Docker Model Runner:
docker model run hf.co/bartowski/Phi-3-medium-4k-instruct-GGUF:Q4_K_M
- Lemonade
How to use bartowski/Phi-3-medium-4k-instruct-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull bartowski/Phi-3-medium-4k-instruct-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Phi-3-medium-4k-instruct-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
On some promts, medium is worse than mini&small?
"Today I own 3 cars but last year I sold 2 cars. How many cars do I own today?"
How is it possible that the 'medium' version often fails at this question, while even the 'mini' version gets it right? (and 'small' too)
It alwost always gives wrong answer: 1 , while other two say: 3
are you using quants for the others as well? does small have quant support?
That's strange either way
are you using quants for the others as well? does small have quant support?
https://ai.azure.com/explore/models?selectedCollection=phi
Here are all the models, you can test each on the right, under "Try it out". I also tested q4km ggufs for mini and medium locally, and get same results.
If it's full weights for all of them and they're still different outputs that's super strange!
Didn't mean to ignore this, just got lost lol
Didn't mean to ignore this, just got lost lol
no, i'm just not sure myself anymore. Because at first i was sure about what's in my first message. But now it seems to answer the question correctly... most of the time.
And btw, sorry for another question, but i just can't figure out why phi models, like this one, only generate text up to around 2500/4096 context and then stop, or just generate nonsense?(instruct mode) I think kobolt.cpp says something like "EOS token triggered!". Same in lm studio or oobabooga.
That does seem curious.. If you have a prompt that triggers it reliable let me know but I'll try to see if I can see it too. If it's happening on multiple platforms that does seem odd..
I assume this doesn't apply to any hosted full weight versions?
No special promt. Just tell it to write some stories or something so it reaches ~2500 context length.
I've been experiencing this since the first day phi-3 came out, and I have no idea why, it seems like I'm the only one, because nobody talks about it. Only phi models do this.
@urtuuuu It is happening with me too. Messed up garbage after 2500 token. Using Q5KM. Trying to change quants.