Instructions to use appvoid/void.0 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 appvoid/void.0 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 appvoid/void.0 # Run inference directly in the terminal: llama cli -hf appvoid/void.0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf appvoid/void.0 # Run inference directly in the terminal: llama cli -hf appvoid/void.0
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 appvoid/void.0 # Run inference directly in the terminal: ./llama-cli -hf appvoid/void.0
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 appvoid/void.0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf appvoid/void.0
Use Docker
docker model run hf.co/appvoid/void.0
- LM Studio
- Jan
- Ollama
How to use appvoid/void.0 with Ollama:
ollama run hf.co/appvoid/void.0
- Unsloth Desktop
- Docker Model Runner
How to use appvoid/void.0 with Docker Model Runner:
docker model run hf.co/appvoid/void.0
- Lemonade
How to use appvoid/void.0 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull appvoid/void.0
Run and chat with the model
lemonade run user.void.0-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
Update README.md
Browse files
README.md
CHANGED
|
@@ -11,6 +11,38 @@ tags:
|
|
| 11 |
- pretrained-from-scratch
|
| 12 |
---
|
| 13 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 14 |
Introducing **void**: our first ever language model, trained from scratch with a novel hybrid tokenizer on 300M high-quality tokens using 4096 as context window. It has around 140m parameters. Future releases are expected to be published in the following weeks.
|
| 15 |
|
| 16 |
**Disclaimer:** Even though the model is based on gemma 3 architecture, the tokenizer is different so you might need to wait until this model can be added to llama.cpp
|
|
|
|
| 11 |
- pretrained-from-scratch
|
| 12 |
---
|
| 13 |
|
| 14 |
+
<style>
|
| 15 |
+
img {
|
| 16 |
+
display: block;
|
| 17 |
+
position: static;
|
| 18 |
+
width: min(76%, 480px);
|
| 19 |
+
height: auto;
|
| 20 |
+
max-width: 100%;
|
| 21 |
+
margin: 3rem auto 2.5rem;
|
| 22 |
+
object-fit: contain;
|
| 23 |
+
|
| 24 |
+
border: 2px solid rgba(255, 255, 255, 0.16);
|
| 25 |
+
border-radius: 1rem;
|
| 26 |
+
outline: none;
|
| 27 |
+
|
| 28 |
+
user-select: none;
|
| 29 |
+
-webkit-user-select: none;
|
| 30 |
+
-moz-user-select: none;
|
| 31 |
+
-webkit-user-drag: none;
|
| 32 |
+
|
| 33 |
+
filter: none !important;
|
| 34 |
+
transform: scale(1) !important;
|
| 35 |
+
animation: none !important;
|
| 36 |
+
box-shadow: none !important;
|
| 37 |
+
|
| 38 |
+
position: relative;
|
| 39 |
+
z-index: 1;
|
| 40 |
+
transform-origin: center;
|
| 41 |
+
}
|
| 42 |
+
</style>
|
| 43 |
+
|
| 44 |
+
<img src="https://huggingface.co/appvoid/void.0-preview/resolve/main/logo.png"/>
|
| 45 |
+
|
| 46 |
Introducing **void**: our first ever language model, trained from scratch with a novel hybrid tokenizer on 300M high-quality tokens using 4096 as context window. It has around 140m parameters. Future releases are expected to be published in the following weeks.
|
| 47 |
|
| 48 |
**Disclaimer:** Even though the model is based on gemma 3 architecture, the tokenizer is different so you might need to wait until this model can be added to llama.cpp
|