Translation
GGUF
Chinese
English
Japanese
streaming-translation
simultaneous-translation
subtitles
speech-translation
llama.cpp
quantized
conversational
Instructions to use febilly/Hy-MT2-1.8B-StreamRevise-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 febilly/Hy-MT2-1.8B-StreamRevise-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 febilly/Hy-MT2-1.8B-StreamRevise-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf febilly/Hy-MT2-1.8B-StreamRevise-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 febilly/Hy-MT2-1.8B-StreamRevise-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf febilly/Hy-MT2-1.8B-StreamRevise-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 febilly/Hy-MT2-1.8B-StreamRevise-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf febilly/Hy-MT2-1.8B-StreamRevise-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 febilly/Hy-MT2-1.8B-StreamRevise-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf febilly/Hy-MT2-1.8B-StreamRevise-GGUF:Q4_K_M
Use Docker
docker model run hf.co/febilly/Hy-MT2-1.8B-StreamRevise-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use febilly/Hy-MT2-1.8B-StreamRevise-GGUF with Ollama:
ollama run hf.co/febilly/Hy-MT2-1.8B-StreamRevise-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use febilly/Hy-MT2-1.8B-StreamRevise-GGUF with Docker Model Runner:
docker model run hf.co/febilly/Hy-MT2-1.8B-StreamRevise-GGUF:Q4_K_M
- Lemonade
How to use febilly/Hy-MT2-1.8B-StreamRevise-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull febilly/Hy-MT2-1.8B-StreamRevise-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Hy-MT2-1.8B-StreamRevise-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
- Xet hash:
- 6fd5d4fac476084d44616af4f667416afc7b9a05fc59fbb4f63f141f1b2937e3
- Size of remote file:
- 1.07 GB
- SHA256:
- eaf0fecb53a50f533377f975ad507294fd504eb94619f2f19119a5e81fdb06b0
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