Instructions to use SEE7/AstheralTranslate-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 SEE7/AstheralTranslate-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 SEE7/AstheralTranslate-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf SEE7/AstheralTranslate-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 SEE7/AstheralTranslate-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf SEE7/AstheralTranslate-GGUF:Q4_K_M
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 SEE7/AstheralTranslate-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf SEE7/AstheralTranslate-GGUF:Q4_K_M
Use Docker
docker model run hf.co/SEE7/AstheralTranslate-GGUF:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use SEE7/AstheralTranslate-GGUF with Ollama:
ollama run hf.co/SEE7/AstheralTranslate-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use SEE7/AstheralTranslate-GGUF with Docker Model Runner:
docker model run hf.co/SEE7/AstheralTranslate-GGUF:Q4_K_M
- Lemonade
How to use SEE7/AstheralTranslate-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull SEE7/AstheralTranslate-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.AstheralTranslate-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
AstheralTranslate GGUF
GGUF quantizations of SEE7/AstheralTranslate, generated with llama.cpp 5676dfbe01e7ebe0387913680eee0ed39bf4a363.
Provided Quants
Measured decimal GB, sorted by file size. Each linked file has passed GGUF structure and upload hash checks.
| Link | Type | Size/GB |
|---|---|---|
| GGUF | imatrix | 0.003 |
| GGUF | i1-IQ1_S | 0.508 |
| GGUF | i1-IQ1_M | 0.531 |
| GGUF | i1-IQ2_XXS | 0.568 |
| GGUF | i1-IQ2_XS | 0.600 |
| GGUF | i1-IQ2_S | 0.650 |
| GGUF | i1-IQ2_M | 0.679 |
| GGUF | i1-Q2_K_S | 0.684 |
| GGUF | i1-Q2_K | 0.720 |
| GGUF | i1-IQ3_XXS | 0.725 |
| GGUF | i1-IQ3_XS | 0.791 |
| GGUF | i1-Q3_K_S | 0.818 |
| GGUF | i1-IQ3_S | 0.818 |
| GGUF | i1-IQ3_M | 0.842 |
| GGUF | i1-Q3_K_M | 0.877 |
| GGUF | i1-Q3_K_L | 0.928 |
| GGUF | i1-IQ4_XS | 0.959 |
| GGUF | i1-IQ4_NL | 1.003 |
| GGUF | i1-Q4_0 | 1.005 |
| GGUF | i1-Q4_K_S | 1.008 |
| GGUF | i1-Q4_K_M | 1.045 |
| GGUF | i1-Q4_1 | 1.090 |
| GGUF | i1-Q5_K_S | 1.177 |
| GGUF | i1-Q5_K_M | 1.199 |
| GGUF | i1-Q6_K | 1.363 |
Calibration
Importance data is collected from real forward passes over a deterministic multilingual and instruction sample of AstheralDataset. Corpus hash, chunk settings, exact tensor formats, and file SHA-256 hashes are recorded in manifest.json.
- Downloads last month
- -
Hardware compatibility
Log In to add your hardware
Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐ Ask for provider support