Text Generation
GGUF
English
Māori
llama.cpp
abteex-ai-labs
aotearoa
general
local-first
lumynax
new-zealand
smollm
sovereign-ai
text
vllm
vllm-compatible
vllm-experimental
nvidia-nim
nim-compatible
nim-candidate
nvidia-nemo
nem
nvidia-nemo-pathway
nem-pathway
nem-convert-required
conversational
Instructions to use AbteeXAILab/lumynax-infused-smollm2-360m-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use AbteeXAILab/lumynax-infused-smollm2-360m-gguf with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="AbteeXAILab/lumynax-infused-smollm2-360m-gguf", filename="smollm2-360m-instruct-q8_0.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use AbteeXAILab/lumynax-infused-smollm2-360m-gguf with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_0 # Run inference directly in the terminal: llama-cli -hf AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_0 # Run inference directly in the terminal: llama-cli -hf AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_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 AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_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 AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_0
Use Docker
docker model run hf.co/AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_0
- LM Studio
- Jan
- vLLM
How to use AbteeXAILab/lumynax-infused-smollm2-360m-gguf with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AbteeXAILab/lumynax-infused-smollm2-360m-gguf" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AbteeXAILab/lumynax-infused-smollm2-360m-gguf", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_0
- Ollama
How to use AbteeXAILab/lumynax-infused-smollm2-360m-gguf with Ollama:
ollama run hf.co/AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_0
- Unsloth Studio
How to use AbteeXAILab/lumynax-infused-smollm2-360m-gguf 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 AbteeXAILab/lumynax-infused-smollm2-360m-gguf 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 AbteeXAILab/lumynax-infused-smollm2-360m-gguf to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for AbteeXAILab/lumynax-infused-smollm2-360m-gguf to start chatting
- Atomic Chat new
- Docker Model Runner
How to use AbteeXAILab/lumynax-infused-smollm2-360m-gguf with Docker Model Runner:
docker model run hf.co/AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_0
- Lemonade
How to use AbteeXAILab/lumynax-infused-smollm2-360m-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull AbteeXAILab/lumynax-infused-smollm2-360m-gguf:Q8_0
Run and chat with the model
lemonade run user.lumynax-infused-smollm2-360m-gguf-Q8_0
List all available models
lemonade list
docs: publish professional LumynaX model card
Browse files- README.md +11 -0
- checksums.sha256 +1 -1
README.md
CHANGED
|
@@ -16,6 +16,17 @@ tags:
|
|
| 16 |
- smollm
|
| 17 |
- sovereign-ai
|
| 18 |
- text
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 19 |
---
|
| 20 |
|
| 21 |
# LumynaX Infused SmolLM2 360M Instruct GGUF
|
|
|
|
| 16 |
- smollm
|
| 17 |
- sovereign-ai
|
| 18 |
- text
|
| 19 |
+
- vllm
|
| 20 |
+
- vllm-compatible
|
| 21 |
+
- vllm-experimental
|
| 22 |
+
- nvidia-nim
|
| 23 |
+
- nim-compatible
|
| 24 |
+
- nim-candidate
|
| 25 |
+
- nvidia-nemo
|
| 26 |
+
- nem
|
| 27 |
+
- nvidia-nemo-pathway
|
| 28 |
+
- nem-pathway
|
| 29 |
+
- nem-convert-required
|
| 30 |
---
|
| 31 |
|
| 32 |
# LumynaX Infused SmolLM2 360M Instruct GGUF
|
checksums.sha256
CHANGED
|
@@ -9,7 +9,7 @@ c46f2b285b76fa0a180e3945a11fe035f318a73168b565973771474fb1b20494 merged_model/P
|
|
| 9 |
5e05007a23fd50cf67d323643af03c20ecf8aacd8728ebb159cfc9163a98e21c ollama/create_ollama_model.ps1
|
| 10 |
84f079674b6370ff673f3308c9759d17e88c94b276d31e470b826357fcf4cd6c ollama/Modelfile
|
| 11 |
1be0702ab536c4e402638faa5fcaffc368a245bf42930f4ece357299eee1e3cd quickstart.py
|
| 12 |
-
|
| 13 |
006cd08485755e0e71386b4a41a1401e8b72b737b7479670fd091976225398b5 release_export_manifest.json
|
| 14 |
2a7ca962dd79646b8470b45ec926ade0a4eb01ebdd93452e6990d8997666e378 requirements.txt
|
| 15 |
48ab3034d0dd401fbc721eb1df3217902fee7dab9078992d66431f09b7750201 smollm2-360m-instruct-q8_0.gguf
|
|
|
|
| 9 |
5e05007a23fd50cf67d323643af03c20ecf8aacd8728ebb159cfc9163a98e21c ollama/create_ollama_model.ps1
|
| 10 |
84f079674b6370ff673f3308c9759d17e88c94b276d31e470b826357fcf4cd6c ollama/Modelfile
|
| 11 |
1be0702ab536c4e402638faa5fcaffc368a245bf42930f4ece357299eee1e3cd quickstart.py
|
| 12 |
+
14829d663ade465d9bdc26ccccf7b6d48969f79a91c6024ac1382e0e9b7bb560 README.md
|
| 13 |
006cd08485755e0e71386b4a41a1401e8b72b737b7479670fd091976225398b5 release_export_manifest.json
|
| 14 |
2a7ca962dd79646b8470b45ec926ade0a4eb01ebdd93452e6990d8997666e378 requirements.txt
|
| 15 |
48ab3034d0dd401fbc721eb1df3217902fee7dab9078992d66431f09b7750201 smollm2-360m-instruct-q8_0.gguf
|