Instructions to use VongolaChouko/Starcannon-Unleashed-12B-v1.0-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use VongolaChouko/Starcannon-Unleashed-12B-v1.0-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("VongolaChouko/Starcannon-Unleashed-12B-v1.0-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use VongolaChouko/Starcannon-Unleashed-12B-v1.0-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 VongolaChouko/Starcannon-Unleashed-12B-v1.0-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf VongolaChouko/Starcannon-Unleashed-12B-v1.0-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 VongolaChouko/Starcannon-Unleashed-12B-v1.0-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf VongolaChouko/Starcannon-Unleashed-12B-v1.0-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 VongolaChouko/Starcannon-Unleashed-12B-v1.0-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf VongolaChouko/Starcannon-Unleashed-12B-v1.0-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 VongolaChouko/Starcannon-Unleashed-12B-v1.0-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf VongolaChouko/Starcannon-Unleashed-12B-v1.0-GGUF:Q4_K_M

Use Docker

docker model run hf.co/VongolaChouko/Starcannon-Unleashed-12B-v1.0-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use VongolaChouko/Starcannon-Unleashed-12B-v1.0-GGUF with Ollama:
```
ollama run hf.co/VongolaChouko/Starcannon-Unleashed-12B-v1.0-GGUF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use VongolaChouko/Starcannon-Unleashed-12B-v1.0-GGUF with Docker Model Runner:
```
docker model run hf.co/VongolaChouko/Starcannon-Unleashed-12B-v1.0-GGUF:Q4_K_M
```

Lemonade

How to use VongolaChouko/Starcannon-Unleashed-12B-v1.0-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull VongolaChouko/Starcannon-Unleashed-12B-v1.0-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Starcannon-Unleashed-12B-v1.0-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

VongolaChouko commited on Oct 30, 2024

Commit

1f54dd5

verified ·

1 Parent(s): fef4011

Update README.md

Browse files

Files changed (1) hide show

README.md +61 -7

README.md CHANGED Viewed

@@ -1,6 +1,5 @@
 ---
 base_model:
-- mistralai/Mistral-Nemo-Instruct-2407
 - nothingiisreal/MN-12B-Starcannon-v3
 - MarinaraSpaghetti/NemoMix-Unleashed-12B
 library_name: transformers
@@ -12,16 +11,71 @@ tags:
 license: cc-by-nc-4.0
 ---
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/6720ed503a24966ac66495e8/fG6Dbcz-Wxh52rTBxt5vN.png)
-# VongolaChouko/Starcannon-Unleashed-12B-v1.0-GGUF
-Static quants of [`VongolaChouko/Starcannon-Unleashed-12B-v1.0`](https://huggingface.co/VongolaChouko/Starcannon-Unleashed-12B-v1.0) .
-This model was converted to GGUF format from [`VongolaChouko/Starcannon-Unleashed-12B-v1.0`](https://huggingface.co/VongolaChouko/Starcannon-Unleashed-12B-v1.0) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
-Refer to the [original model card](https://huggingface.co/VongolaChouko/Starcannon-Unleashed-12B-v1.0) for more details on the model.
-## Use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)
 ```bash

 ---
 base_model:
 - nothingiisreal/MN-12B-Starcannon-v3
 - MarinaraSpaghetti/NemoMix-Unleashed-12B
 library_name: transformers
 license: cc-by-nc-4.0
 ---
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6720ed503a24966ac66495e8/HXc0AxPLkoIC1fy0Pb3Pb.png)
+Starcannon-Unleashed-12B-v1.0-GGUF
+==================================
+Static quants of [**VongolaChouko/Starcannon-Unleashed-12B-v1.0**](https://huggingface.co/VongolaChouko/Starcannon-Unleashed-12B-v1.0).
+This model was converted to GGUF format from [VongolaChouko/Starcannon-Unleashed-12B-v1.0](https://huggingface.co/VongolaChouko/Starcannon-Unleashed-12B-v1.0) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
+Refer to the [original model card](https://huggingface.co/VongolaChouko/Starcannon-Unleashed-12B-v1.0) for more details on the model.
+**I recommend using them with [koboldcpp](https://github.com/LostRuins/koboldcpp). You can find their latest release here: [koboldcpp-1.76](https://github.com/LostRuins/koboldcpp/releases)**
+<hr/>
+## Download a file (not the whole branch) from below:
+| Filename | Quant type | File Size | Split | Description |
+| -------- | ---------- | --------- | ----- | ----------- |
+| [Starcannon-Unleashed-12B-v1.0-FP16.gguf](https://huggingface.co/VongolaChouko/Starcannon-Unleashed-12B-v1.0-GGUF/blob/main/Starcannon-Unleashed-12B-v1.0-FP16.gguf) | f16 | 24.50GB | false | Full F16 weights. |
+| [Mistral-Nemo-Instruct-2407-Q8_0.gguf](https://huggingface.co/bartowski/Mistral-Nemo-Instruct-2407-GGUF/blob/main/Mistral-Nemo-Instruct-2407-Q8_0.gguf) | Q8_0 | 13.02GB | false | Extremely high quality, generally unneeded but max available quant. |
+| [Starcannon-Unleashed-12B-v1.0-Q6_K.gguf](https://huggingface.co/VongolaChouko/Starcannon-Unleashed-12B-v1.0-GGUF/blob/main/Starcannon-Unleashed-12B-v1.0-Q6_K.gguf) | Q6_K | 10.06GB | false | Very high quality, near perfect, *recommended*. |
+| [Mistral-Nemo-Instruct-2407-Q5_K_L.gguf](https://huggingface.co/bartowski/Mistral-Nemo-Instruct-2407-GGUF/blob/main/Mistral-Nemo-Instruct-2407-Q5_K_L.gguf) | Q5_K_L | 9.14GB | false | Uses Q8_0 for embed and output weights. High quality, *recommended*. |
+| [Mistral-Nemo-Instruct-2407-Q5_K_M.gguf](https://huggingface.co/bartowski/Mistral-Nemo-Instruct-2407-GGUF/blob/main/Mistral-Nemo-Instruct-2407-Q5_K_M.gguf) | Q5_K_M | 8.73GB | false | High quality, *recommended*. |
+| [Mistral-Nemo-Instruct-2407-Q5_K_S.gguf](https://huggingface.co/bartowski/Mistral-Nemo-Instruct-2407-GGUF/blob/main/Mistral-Nemo-Instruct-2407-Q5_K_S.gguf) | Q5_K_S | 8.52GB | false | High quality, *recommended*. |
+| [Mistral-Nemo-Instruct-2407-Q4_K_L.gguf](https://huggingface.co/bartowski/Mistral-Nemo-Instruct-2407-GGUF/blob/main/Mistral-Nemo-Instruct-2407-Q4_K_L.gguf) | Q4_K_L | 7.98GB | false | Uses Q8_0 for embed and output weights. Good quality, *recommended*. |
+| [Mistral-Nemo-Instruct-2407-Q4_K_M.gguf](https://huggingface.co/bartowski/Mistral-Nemo-Instruct-2407-GGUF/blob/main/Mistral-Nemo-Instruct-2407-Q4_K_M.gguf) | Q4_K_M | 7.48GB | false | Good quality, default size for must use cases, *recommended*. |
+| [Mistral-Nemo-Instruct-2407-Q3_K_XL.gguf](https://huggingface.co/bartowski/Mistral-Nemo-Instruct-2407-GGUF/blob/main/Mistral-Nemo-Instruct-2407-Q3_K_XL.gguf) | Q3_K_XL | 7.15GB | false | Uses Q8_0 for embed and output weights. Lower quality but usable, good for low RAM availability. |
+| [Mistral-Nemo-Instruct-2407-Q4_K_S.gguf](https://huggingface.co/bartowski/Mistral-Nemo-Instruct-2407-GGUF/blob/main/Mistral-Nemo-Instruct-2407-Q4_K_S.gguf) | Q4_K_S | 7.12GB | false | Slightly lower quality with more space savings, *recommended*. |
+| [Mistral-Nemo-Instruct-2407-Q4_0.gguf](https://huggingface.co/bartowski/Mistral-Nemo-Instruct-2407-GGUF/blob/main/Mistral-Nemo-Instruct-2407-Q4_0.gguf) | Q4_0 | 7.09GB | false | Legacy format, generally not worth using over similarly sized formats |
+| [Mistral-Nemo-Instruct-2407-Q4_0_8_8.gguf](https://huggingface.co/bartowski/Mistral-Nemo-Instruct-2407-GGUF/blob/main/Mistral-Nemo-Instruct-2407-Q4_0_8_8.gguf) | Q4_0_8_8 | 7.07GB | false | Optimized for ARM and CPU inference, much faster than Q4_0 at similar quality. |
+| [Mistral-Nemo-Instruct-2407-Q4_0_4_8.gguf](https://huggingface.co/bartowski/Mistral-Nemo-Instruct-2407-GGUF/blob/main/Mistral-Nemo-Instruct-2407-Q4_0_4_8.gguf) | Q4_0_4_8 | 7.07GB | false | Optimized for ARM and CPU inference, much faster than Q4_0 at similar quality. |
+| [Mistral-Nemo-Instruct-2407-Q4_0_4_4.gguf](https://huggingface.co/bartowski/Mistral-Nemo-Instruct-2407-GGUF/blob/main/Mistral-Nemo-Instruct-2407-Q4_0_4_4.gguf) | Q4_0_4_4 | 7.07GB | false | Optimized for ARM and CPU inference, much faster than Q4_0 at similar quality. |
+| [Mistral-Nemo-Instruct-2407-IQ4_XS.gguf](https://huggingface.co/bartowski/Mistral-Nemo-Instruct-2407-GGUF/blob/main/Mistral-Nemo-Instruct-2407-IQ4_XS.gguf) | IQ4_XS | 6.74GB | false | Decent quality, smaller than Q4_K_S with similar performance, *recommended*. |
+| [Mistral-Nemo-Instruct-2407-Q3_K_L.gguf](https://huggingface.co/bartowski/Mistral-Nemo-Instruct-2407-GGUF/blob/main/Mistral-Nemo-Instruct-2407-Q3_K_L.gguf) | Q3_K_L | 6.56GB | false | Lower quality but usable, good for low RAM availability. |
+| [Mistral-Nemo-Instruct-2407-Q3_K_M.gguf](https://huggingface.co/bartowski/Mistral-Nemo-Instruct-2407-GGUF/blob/main/Mistral-Nemo-Instruct-2407-Q3_K_M.gguf) | Q3_K_M | 6.08GB | false | Low quality. |
+| [Mistral-Nemo-Instruct-2407-IQ3_M.gguf](https://huggingface.co/bartowski/Mistral-Nemo-Instruct-2407-GGUF/blob/main/Mistral-Nemo-Instruct-2407-IQ3_M.gguf) | IQ3_M | 5.72GB | false | Medium-low quality, new method with decent performance comparable to Q3_K_M. |
+| [Mistral-Nemo-Instruct-2407-Q3_K_S.gguf](https://huggingface.co/bartowski/Mistral-Nemo-Instruct-2407-GGUF/blob/main/Mistral-Nemo-Instruct-2407-Q3_K_S.gguf) | Q3_K_S | 5.53GB | false | Low quality, not recommended. |
+| [Mistral-Nemo-Instruct-2407-Q2_K_L.gguf](https://huggingface.co/bartowski/Mistral-Nemo-Instruct-2407-GGUF/blob/main/Mistral-Nemo-Instruct-2407-Q2_K_L.gguf) | Q2_K_L | 5.45GB | false | Uses Q8_0 for embed and output weights. Very low quality but surprisingly usable. |
+| [Mistral-Nemo-Instruct-2407-IQ3_XS.gguf](https://huggingface.co/bartowski/Mistral-Nemo-Instruct-2407-GGUF/blob/main/Mistral-Nemo-Instruct-2407-IQ3_XS.gguf) | IQ3_XS | 5.31GB | false | Lower quality, new method with decent performance, slightly better than Q3_K_S. |
+| [Mistral-Nemo-Instruct-2407-Q2_K.gguf](https://huggingface.co/bartowski/Mistral-Nemo-Instruct-2407-GGUF/blob/main/Mistral-Nemo-Instruct-2407-Q2_K.gguf) | Q2_K | 4.79GB | false | Very low quality but surprisingly usable. |
+| [Mistral-Nemo-Instruct-2407-IQ2_M.gguf](https://huggingface.co/bartowski/Mistral-Nemo-Instruct-2407-GGUF/blob/main/Mistral-Nemo-Instruct-2407-IQ2_M.gguf) | IQ2_M | 4.44GB | false | Relatively low quality, uses SOTA techniques to be surprisingly usable. |
+## Instruct
+Both ChatML and Mistral should work fine. Personally, I tested this using ChatML. I found that I like the model's responses better when I use this format. Try to test it out and observe which one you like best. :D
+## Settings
+I recommend using these setings:
+[Starcannon-Unleashed-12B-v1.0-ST-Formatting-2024-10-29.json](https://huggingface.co/VongolaChouko/Starcannon-Unleashed-12B-v1.0/blob/main/Starcannon-Unleashed-12B-v1.0-ST-Formatting-2024-10-29.json)
+**IMPORTANT: Open Silly Tavern and use "Master Import", which can be found under "A" tab — Advanced Formatting. Replace the "INSERT WORLD HERE" placeholders with the world/universe in which your charcater belongs to. If not applicable, just remove that part.**
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6720ed503a24966ac66495e8/hAr6qvG3iWKKXOUP9Sy07.png)
+Temperature 1.15 - 1.25 is good, but lower should also work well, as long as you also tweak the Min P and XTC to ensure the model won't choke. Play around with it to see what suits your taste.
+This is a modified version of MarinaraSpaghetti's Mistral-Small-Correct.json, transformed into ChatML.
+You can find the original version here: [MarinaraSpaghetti/SillyTavern-Settings](https://huggingface.co/MarinaraSpaghetti/SillyTavern-Settings/tree/main/Customized)
+## To use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)
 ```bash