Instructions to use tianclll/AceTranslatePro-models 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 tianclll/AceTranslatePro-models 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 tianclll/AceTranslatePro-models:Q3_K_M # Run inference directly in the terminal: llama cli -hf tianclll/AceTranslatePro-models:Q3_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tianclll/AceTranslatePro-models:Q3_K_M # Run inference directly in the terminal: llama cli -hf tianclll/AceTranslatePro-models:Q3_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 tianclll/AceTranslatePro-models:Q3_K_M # Run inference directly in the terminal: ./llama-cli -hf tianclll/AceTranslatePro-models:Q3_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 tianclll/AceTranslatePro-models:Q3_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf tianclll/AceTranslatePro-models:Q3_K_M
Use Docker
docker model run hf.co/tianclll/AceTranslatePro-models:Q3_K_M
- LM Studio
- Jan
- Ollama
How to use tianclll/AceTranslatePro-models with Ollama:
ollama run hf.co/tianclll/AceTranslatePro-models:Q3_K_M
- Unsloth Studio
How to use tianclll/AceTranslatePro-models with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for tianclll/AceTranslatePro-models to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for tianclll/AceTranslatePro-models to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for tianclll/AceTranslatePro-models to start chatting
- Pi
How to use tianclll/AceTranslatePro-models with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf tianclll/AceTranslatePro-models:Q3_K_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "tianclll/AceTranslatePro-models:Q3_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- OpenClaw new
How to use tianclll/AceTranslatePro-models with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf tianclll/AceTranslatePro-models:Q3_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "tianclll/AceTranslatePro-models:Q3_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
- Docker Model Runner
How to use tianclll/AceTranslatePro-models with Docker Model Runner:
docker model run hf.co/tianclll/AceTranslatePro-models:Q3_K_M
- Lemonade
How to use tianclll/AceTranslatePro-models with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tianclll/AceTranslatePro-models:Q3_K_M
Run and chat with the model
lemonade run user.AceTranslatePro-models-Q3_K_M
List all available models
lemonade list
- Hermes Agent
How to use tianclll/AceTranslatePro-models with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf tianclll/AceTranslatePro-models:Q3_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default tianclll/AceTranslatePro-models:Q3_K_M
Run Hermes
hermes
- Atomic Chat
File size: 1,668 Bytes
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library_name: generic
license: mit
pipeline_tag: other
---
# AceTranslatePro Models
AceTranslatePro ็ๆจกๅๆไปถๅ
ใๅ
ๅซ็ฟป่ฏใOCRใ็้ขๅๆใ่ฏญ้ณ่ฏๅซใๅพ็็ซๆญฃ็ญๆๆๆจกๅใ
## ็ฎๅฝ็ปๆ
```
models/
โโโ translation/ # ็ฟป่ฏๆจกๅ๏ผGGUF๏ผ
โ โโโ Hy-MT2-1.8B-Q4_K_M.gguf # ็ฟป่ฏๆจกๅ๏ผ้ป่ฎค๏ผๆจ่๏ผ
โ โโโ Hy-MT2-1.8B-Q6_K.gguf # ็ฟป่ฏๆจกๅ๏ผๆด้ซ็ฒพๅบฆ๏ผ
โ โโโ HY-MT1.5-1.8B-Q4_K_M.gguf
โ โโโ HY-MT1.5-1.8B-Q6_K.gguf
โโโ VLM/ # ๅคๆจกๆๅ
ฌๅผ่ฏๅซ๏ผGGUF๏ผ
โ โโโ PaddleOCR-VL-1.6-GGUF.gguf
โ โโโ PaddleOCR-VL-1.6-GGUF-mmproj.gguf
โโโ layout/
โ โโโ pp_doclayoutv2.onnx # ็้ขๅๆๆจกๅ
โโโ ocr/ # OCR ๆจกๅ๏ผONNX๏ผ
โ โโโ tiny/ # ่ฝป้็๏ผ้ป่ฎค๏ผ
โ โ โโโ det/det.onnx
โ โ โโโ rec/rec.onnx
โ โ โโโ cls/cls.onnx
โ โโโ small/ # ไธญ็ญ็
โ โโโ medium/ # ้ซ็ฒพๅบฆ็
โ โโโ ppocrv6_dict.txt
โโโ ASR/
โ โโโ model_quant.onnx # ่ฏญ้ณ่ฏๅซ๏ผSenseVoiceSmall๏ผ
โ โโโ am.mvn # CMVN ๅฝไธๅ
โ โโโ tokens.json
โโโ uvdoc/
โ โโโ UVDoc_grid.onnx # ๅพ็็ซๆญฃ
โโโ orientation/
โโโ rapid_orientation.onnx # ๆนๅๆฃๆต
โโโ summary/
โโโ qwen2.5-1.5b-instruct-q2_k.gguf # ็ๆๆ่ฆ
```
## ไฝฟ็จๆนๆณ
ๅฐ `models/` ็ฎๅฝๆพๅฐ AceTranslatePro.exe ๅ็บง็ฎๅฝๅณๅฏใ |