Instructions to use mradermacher/Cakrawala-123B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mradermacher/Cakrawala-123B-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mradermacher/Cakrawala-123B-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use mradermacher/Cakrawala-123B-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/Cakrawala-123B-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf mradermacher/Cakrawala-123B-GGUF:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf mradermacher/Cakrawala-123B-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf mradermacher/Cakrawala-123B-GGUF:Q2_K
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/Cakrawala-123B-GGUF:Q2_K # Run inference directly in the terminal: ./llama-cli -hf mradermacher/Cakrawala-123B-GGUF:Q2_K
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/Cakrawala-123B-GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf mradermacher/Cakrawala-123B-GGUF:Q2_K
Use Docker
docker model run hf.co/mradermacher/Cakrawala-123B-GGUF:Q2_K
- LM Studio
- Jan
- Ollama
How to use mradermacher/Cakrawala-123B-GGUF with Ollama:
ollama run hf.co/mradermacher/Cakrawala-123B-GGUF:Q2_K
- Unsloth Desktop
- Docker Model Runner
How to use mradermacher/Cakrawala-123B-GGUF with Docker Model Runner:
docker model run hf.co/mradermacher/Cakrawala-123B-GGUF:Q2_K
- Lemonade
How to use mradermacher/Cakrawala-123B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mradermacher/Cakrawala-123B-GGUF:Q2_K
Run and chat with the model
lemonade run user.Cakrawala-123B-GGUF-Q2_K
List all available models
lemonade list
- Atomic Chat
auto-patch README.md
Browse files
README.md
CHANGED
|
@@ -34,7 +34,14 @@ more details, including on how to concatenate multi-part files.
|
|
| 34 |
| Link | Type | Size/GB | Notes |
|
| 35 |
|:-----|:-----|--------:|:------|
|
| 36 |
| [GGUF](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q2_K.gguf) | Q2_K | 45.3 | |
|
|
|
|
|
|
|
|
|
|
| 37 |
| [PART 1](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q4_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q4_K_S.gguf.part2of2) | Q4_K_S | 69.7 | fast, recommended |
|
|
|
|
|
|
|
|
|
|
|
|
|
| 38 |
| [PART 1](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q8_0.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q8_0.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q8_0.gguf.part3of3) | Q8_0 | 130.4 | fast, best quality |
|
| 39 |
|
| 40 |
Here is a handy graph by ikawrakow comparing some lower-quality quant
|
|
|
|
| 34 |
| Link | Type | Size/GB | Notes |
|
| 35 |
|:-----|:-----|--------:|:------|
|
| 36 |
| [GGUF](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q2_K.gguf) | Q2_K | 45.3 | |
|
| 37 |
+
| [PART 1](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q3_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q3_K_S.gguf.part2of2) | Q3_K_S | 52.9 | |
|
| 38 |
+
| [PART 1](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q3_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q3_K_M.gguf.part2of2) | Q3_K_M | 59.2 | lower quality |
|
| 39 |
+
| [PART 1](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q3_K_L.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q3_K_L.gguf.part2of2) | Q3_K_L | 64.7 | |
|
| 40 |
| [PART 1](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q4_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q4_K_S.gguf.part2of2) | Q4_K_S | 69.7 | fast, recommended |
|
| 41 |
+
| [PART 1](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q4_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q4_K_M.gguf.part2of2) | Q4_K_M | 73.3 | fast, recommended |
|
| 42 |
+
| [PART 1](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q5_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q5_K_S.gguf.part2of2) | Q5_K_S | 84.5 | |
|
| 43 |
+
| [PART 1](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q5_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q5_K_M.gguf.part2of2) | Q5_K_M | 86.6 | |
|
| 44 |
+
| [PART 1](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q6_K.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q6_K.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q6_K.gguf.part3of3) | Q6_K | 100.7 | very good quality |
|
| 45 |
| [PART 1](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q8_0.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q8_0.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/Cakrawala-123B-GGUF/resolve/main/Cakrawala-123B.Q8_0.gguf.part3of3) | Q8_0 | 130.4 | fast, best quality |
|
| 46 |
|
| 47 |
Here is a handy graph by ikawrakow comparing some lower-quality quant
|