Instructions to use tensorblock/Apollo-7B-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 tensorblock/Apollo-7B-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 tensorblock/Apollo-7B-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/Apollo-7B-GGUF:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tensorblock/Apollo-7B-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/Apollo-7B-GGUF:Q2_K
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 tensorblock/Apollo-7B-GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama cli -hf tensorblock/Apollo-7B-GGUF:Q2_K
Use Docker
docker model run hf.co/tensorblock/Apollo-7B-GGUF:Q2_K
- Llama new
- LM Studio
- Jan
- Ollama
How to use tensorblock/Apollo-7B-GGUF with Ollama:
ollama run hf.co/tensorblock/Apollo-7B-GGUF:Q2_K
- Unsloth Desktop
- Docker Model Runner
How to use tensorblock/Apollo-7B-GGUF with Docker Model Runner:
docker model run hf.co/tensorblock/Apollo-7B-GGUF:Q2_K
- Lemonade
How to use tensorblock/Apollo-7B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tensorblock/Apollo-7B-GGUF:Q2_K
Run and chat with the model
lemonade run user.Apollo-7B-GGUF-Q2_K
List all available models
lemonade list
- Atomic Chat
Download Apollo-7B-Q3_K_M.gguf from tensorblock/Apollo-7B-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 4.37 GB
-
https://huggingface.co/tensorblock/Apollo-7B-GGUF/resolve/main/Apollo-7B-Q3_K_M.gguf
- Command line
-
hf download hf://tensorblock/Apollo-7B-GGUF/Apollo-7B-Q3_K_M.gguf
-
curl -L -o Apollo-7B-Q3_K_M.gguf https://huggingface.co/tensorblock/Apollo-7B-GGUF/resolve/main/Apollo-7B-Q3_K_M.gguf
4.37 GB
- Xet hash:
- dfedf438fa24c4b400e0b12b551f1dee69554b5cdace6d88a1a5dcbaeb38cb9c
- Size of remote file:
- 4.37 GB
- SHA256:
- a3a728b06623fa9ac1fa0d4d5c6b040ef7c5cd26bd9b1ba9b2c2b0ed2b795c53
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