Instructions to use Aakash010/MedGemma_FineTuned 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 Aakash010/MedGemma_FineTuned 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 Aakash010/MedGemma_FineTuned:Q4_K_M # Run inference directly in the terminal: llama cli -hf Aakash010/MedGemma_FineTuned:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Aakash010/MedGemma_FineTuned:Q4_K_M # Run inference directly in the terminal: llama cli -hf Aakash010/MedGemma_FineTuned:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf Aakash010/MedGemma_FineTuned:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf Aakash010/MedGemma_FineTuned:Q4_K_M
Use Docker
docker model run hf.co/Aakash010/MedGemma_FineTuned:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use Aakash010/MedGemma_FineTuned with Ollama:
ollama run hf.co/Aakash010/MedGemma_FineTuned:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use Aakash010/MedGemma_FineTuned with Docker Model Runner:
docker model run hf.co/Aakash010/MedGemma_FineTuned:Q4_K_M
- Lemonade
How to use Aakash010/MedGemma_FineTuned with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Aakash010/MedGemma_FineTuned:Q4_K_M
Run and chat with the model
lemonade run user.MedGemma_FineTuned-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download tokenizer.json from Aakash010/MedGemma_FineTuned: direct link, hf CLI and curl.
- Browser
- Download file 33.4 MB
-
https://huggingface.co/Aakash010/MedGemma_FineTuned/resolve/main/tokenizer.json
- Command line
-
hf download hf://Aakash010/MedGemma_FineTuned/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Aakash010/MedGemma_FineTuned/resolve/main/tokenizer.json
33.4 MB
- Xet hash:
- c4c7aa84fb94a696d78f2bde62590a25b6741b7365ed842f9310b5dcab71d95d
- Size of remote file:
- 33.4 MB
- SHA256:
- 4667f2089529e8e7657cfb6d1c19910ae71ff5f28aa7ab2ff2763330affad795
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