Instructions to use Solstice-AI/Athena-27B-UltraEfficient with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Solstice-AI/Athena-27B-UltraEfficient with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Solstice-AI/Athena-27B-UltraEfficient")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Solstice-AI/Athena-27B-UltraEfficient", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Solstice-AI/Athena-27B-UltraEfficient 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 Solstice-AI/Athena-27B-UltraEfficient:Q5_K_M
# Run inference directly in the terminal:
llama cli -hf Solstice-AI/Athena-27B-UltraEfficient:Q5_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Solstice-AI/Athena-27B-UltraEfficient:Q5_K_M
# Run inference directly in the terminal:
llama cli -hf Solstice-AI/Athena-27B-UltraEfficient:Q5_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 Solstice-AI/Athena-27B-UltraEfficient:Q5_K_M
# Run inference directly in the terminal:
./llama-cli -hf Solstice-AI/Athena-27B-UltraEfficient:Q5_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 Solstice-AI/Athena-27B-UltraEfficient:Q5_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Solstice-AI/Athena-27B-UltraEfficient:Q5_K_M

Use Docker

docker model run hf.co/Solstice-AI/Athena-27B-UltraEfficient:Q5_K_M

LM Studio
Jan

vLLM

How to use Solstice-AI/Athena-27B-UltraEfficient with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Solstice-AI/Athena-27B-UltraEfficient"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Solstice-AI/Athena-27B-UltraEfficient",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Solstice-AI/Athena-27B-UltraEfficient:Q5_K_M

SGLang

How to use Solstice-AI/Athena-27B-UltraEfficient with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Solstice-AI/Athena-27B-UltraEfficient" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Solstice-AI/Athena-27B-UltraEfficient",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Solstice-AI/Athena-27B-UltraEfficient" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Solstice-AI/Athena-27B-UltraEfficient",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Ollama
How to use Solstice-AI/Athena-27B-UltraEfficient with Ollama:
```
ollama run hf.co/Solstice-AI/Athena-27B-UltraEfficient:Q5_K_M
```

Unsloth Studio

How to use Solstice-AI/Athena-27B-UltraEfficient 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 Solstice-AI/Athena-27B-UltraEfficient 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 Solstice-AI/Athena-27B-UltraEfficient to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Solstice-AI/Athena-27B-UltraEfficient to start chatting

Docker Model Runner
How to use Solstice-AI/Athena-27B-UltraEfficient with Docker Model Runner:
```
docker model run hf.co/Solstice-AI/Athena-27B-UltraEfficient:Q5_K_M
```

Lemonade

How to use Solstice-AI/Athena-27B-UltraEfficient with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Solstice-AI/Athena-27B-UltraEfficient:Q5_K_M

Run and chat with the model

lemonade run user.Athena-27B-UltraEfficient-Q5_K_M

List all available models

lemonade list

Atomic Chat

Shreyan Gondaliya commited on Jul 21

Commit

bb030ca

verified ·

1 Parent(s): 7a99b98

Update README.md

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README.md +3 -1

README.md CHANGED Viewed

@@ -82,4 +82,6 @@ python -m vllm.entrypoints.openai.api_server \
     --model shreyan35/Athena-27B-UltraEfficient \
     --gpu-memory-utilization 0.90 \
     --max-model-len 32768 \
-    --enable-prefix-caching

     --model shreyan35/Athena-27B-UltraEfficient \
     --gpu-memory-utilization 0.90 \
     --max-model-len 32768 \
+    --enable-prefix-caching
+### On top of all this, it also maintains and infact improves its LMSYS Chatbot Arena Elo from its parent model, ~1403 _just_ behind Claude Opus 4.6