Instructions to use mradermacher/TL-RegMix-CLM-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mradermacher/TL-RegMix-CLM-GGUF with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mradermacher/TL-RegMix-CLM-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use mradermacher/TL-RegMix-CLM-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 mradermacher/TL-RegMix-CLM-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf mradermacher/TL-RegMix-CLM-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 mradermacher/TL-RegMix-CLM-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf mradermacher/TL-RegMix-CLM-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 mradermacher/TL-RegMix-CLM-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf mradermacher/TL-RegMix-CLM-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 mradermacher/TL-RegMix-CLM-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf mradermacher/TL-RegMix-CLM-GGUF:Q4_K_M
Use Docker
docker model run hf.co/mradermacher/TL-RegMix-CLM-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use mradermacher/TL-RegMix-CLM-GGUF with Ollama:
ollama run hf.co/mradermacher/TL-RegMix-CLM-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use mradermacher/TL-RegMix-CLM-GGUF with Docker Model Runner:
docker model run hf.co/mradermacher/TL-RegMix-CLM-GGUF:Q4_K_M
- Lemonade
How to use mradermacher/TL-RegMix-CLM-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mradermacher/TL-RegMix-CLM-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.TL-RegMix-CLM-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download TL-RegMix-CLM.Q4_K_M.gguf from mradermacher/TL-RegMix-CLM-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 668 MB
-
https://huggingface.co/mradermacher/TL-RegMix-CLM-GGUF/resolve/main/TL-RegMix-CLM.Q4_K_M.gguf
- Command line
-
hf download hf://mradermacher/TL-RegMix-CLM-GGUF/TL-RegMix-CLM.Q4_K_M.gguf
-
curl -L -o TL-RegMix-CLM.Q4_K_M.gguf https://huggingface.co/mradermacher/TL-RegMix-CLM-GGUF/resolve/main/TL-RegMix-CLM.Q4_K_M.gguf
668 MB
- Xet hash:
- 1949a09ea342602a61579063c0166677a430c3c22959decfd63894ca7a420e37
- Size of remote file:
- 668 MB
- SHA256:
- 99da614ff067afa7911fe44c6a2f51ed2ebcc3b2193a638acc9c059b7a4732bb
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