Instructions to use askmyteapot/Meta-Llama-3-70B-Instruct-abliterated-v3.5-IQ4_XS 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 askmyteapot/Meta-Llama-3-70B-Instruct-abliterated-v3.5-IQ4_XS 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 askmyteapot/Meta-Llama-3-70B-Instruct-abliterated-v3.5-IQ4_XS:IQ4_XS # Run inference directly in the terminal: llama cli -hf askmyteapot/Meta-Llama-3-70B-Instruct-abliterated-v3.5-IQ4_XS:IQ4_XS
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf askmyteapot/Meta-Llama-3-70B-Instruct-abliterated-v3.5-IQ4_XS:IQ4_XS # Run inference directly in the terminal: llama cli -hf askmyteapot/Meta-Llama-3-70B-Instruct-abliterated-v3.5-IQ4_XS:IQ4_XS
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 askmyteapot/Meta-Llama-3-70B-Instruct-abliterated-v3.5-IQ4_XS:IQ4_XS # Run inference directly in the terminal: ./llama-cli -hf askmyteapot/Meta-Llama-3-70B-Instruct-abliterated-v3.5-IQ4_XS:IQ4_XS
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 askmyteapot/Meta-Llama-3-70B-Instruct-abliterated-v3.5-IQ4_XS:IQ4_XS # Run inference directly in the terminal: ./build/bin/llama-cli -hf askmyteapot/Meta-Llama-3-70B-Instruct-abliterated-v3.5-IQ4_XS:IQ4_XS
Use Docker
docker model run hf.co/askmyteapot/Meta-Llama-3-70B-Instruct-abliterated-v3.5-IQ4_XS:IQ4_XS
- LM Studio
- Jan
- Ollama
How to use askmyteapot/Meta-Llama-3-70B-Instruct-abliterated-v3.5-IQ4_XS with Ollama:
ollama run hf.co/askmyteapot/Meta-Llama-3-70B-Instruct-abliterated-v3.5-IQ4_XS:IQ4_XS
- Unsloth Desktop
- Docker Model Runner
How to use askmyteapot/Meta-Llama-3-70B-Instruct-abliterated-v3.5-IQ4_XS with Docker Model Runner:
docker model run hf.co/askmyteapot/Meta-Llama-3-70B-Instruct-abliterated-v3.5-IQ4_XS:IQ4_XS
- Lemonade
How to use askmyteapot/Meta-Llama-3-70B-Instruct-abliterated-v3.5-IQ4_XS with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull askmyteapot/Meta-Llama-3-70B-Instruct-abliterated-v3.5-IQ4_XS:IQ4_XS
Run and chat with the model
lemonade run user.Meta-Llama-3-70B-Instruct-abliterated-v3.5-IQ4_XS-IQ4_XS
List all available models
lemonade list
- Atomic Chat
Download model_ggml_q8_0.gguf.data from askmyteapot/Meta-Llama-3-70B-Instruct-abliterated-v3.5-IQ4_XS: direct link, hf CLI and curl.
- Browser
- Download file 24.9 MB
-
https://huggingface.co/askmyteapot/Meta-Llama-3-70B-Instruct-abliterated-v3.5-IQ4_XS/resolve/main/model_ggml_q8_0.gguf.data
- Command line
-
hf download hf://askmyteapot/Meta-Llama-3-70B-Instruct-abliterated-v3.5-IQ4_XS/model_ggml_q8_0.gguf.data
-
curl -L -o model_ggml_q8_0.gguf.data https://huggingface.co/askmyteapot/Meta-Llama-3-70B-Instruct-abliterated-v3.5-IQ4_XS/resolve/main/model_ggml_q8_0.gguf.data
24.9 MB
- Xet hash:
- b69e20d6e0703e093165dbf173cc85b5d74d9ddcdc478409cbc6df872728b956
- Size of remote file:
- 24.9 MB
- SHA256:
- 607e281f6aa1029a740d85072d3b461234929b31a9b3a69b250ad96ee8a78b34
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