Instructions to use austinaguilar/O2M_MDGPT_3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use austinaguilar/O2M_MDGPT_3B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("austinaguilar/O2M_MDGPT_3B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use austinaguilar/O2M_MDGPT_3B 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 austinaguilar/O2M_MDGPT_3B:Q4_K_M # Run inference directly in the terminal: llama cli -hf austinaguilar/O2M_MDGPT_3B:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf austinaguilar/O2M_MDGPT_3B:Q4_K_M # Run inference directly in the terminal: llama cli -hf austinaguilar/O2M_MDGPT_3B: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 austinaguilar/O2M_MDGPT_3B:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf austinaguilar/O2M_MDGPT_3B:Q4_K_M
Use Docker
docker model run hf.co/austinaguilar/O2M_MDGPT_3B:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use austinaguilar/O2M_MDGPT_3B with Ollama:
ollama run hf.co/austinaguilar/O2M_MDGPT_3B:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use austinaguilar/O2M_MDGPT_3B with Docker Model Runner:
docker model run hf.co/austinaguilar/O2M_MDGPT_3B:Q4_K_M
- Lemonade
How to use austinaguilar/O2M_MDGPT_3B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull austinaguilar/O2M_MDGPT_3B:Q4_K_M
Run and chat with the model
lemonade run user.O2M_MDGPT_3B-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download tokenizer.json from austinaguilar/O2M_MDGPT_3B: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/austinaguilar/O2M_MDGPT_3B/resolve/main/tokenizer.json
- Command line
-
hf download hf://austinaguilar/O2M_MDGPT_3B/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/austinaguilar/O2M_MDGPT_3B/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- 1f070f8246b182cca3cde3d1e4c6d31efe0899e10cdd3d19e863890776df994a
- Size of remote file:
- 17.2 MB
- SHA256:
- 384a7e7c676f7be2e5d2e8449c508be9b00e5b18c5b3c39ebc626e96b3f4b988
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.