Instructions to use Pippinlitli/evolva-molecular-slm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Pippinlitli/evolva-molecular-slm with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Pippinlitli/evolva-molecular-slm", filename="model.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 Pippinlitli/evolva-molecular-slm 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 Pippinlitli/evolva-molecular-slm # Run inference directly in the terminal: llama cli -hf Pippinlitli/evolva-molecular-slm
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Pippinlitli/evolva-molecular-slm # Run inference directly in the terminal: llama cli -hf Pippinlitli/evolva-molecular-slm
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 Pippinlitli/evolva-molecular-slm # Run inference directly in the terminal: ./llama-cli -hf Pippinlitli/evolva-molecular-slm
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 Pippinlitli/evolva-molecular-slm # Run inference directly in the terminal: ./build/bin/llama-cli -hf Pippinlitli/evolva-molecular-slm
Use Docker
docker model run hf.co/Pippinlitli/evolva-molecular-slm
- LM Studio
- Jan
- vLLM
How to use Pippinlitli/evolva-molecular-slm with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Pippinlitli/evolva-molecular-slm" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Pippinlitli/evolva-molecular-slm", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Pippinlitli/evolva-molecular-slm
- Ollama
How to use Pippinlitli/evolva-molecular-slm with Ollama:
ollama run hf.co/Pippinlitli/evolva-molecular-slm
- Unsloth Studio
How to use Pippinlitli/evolva-molecular-slm 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 Pippinlitli/evolva-molecular-slm 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 Pippinlitli/evolva-molecular-slm to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Pippinlitli/evolva-molecular-slm to start chatting
- Pi
How to use Pippinlitli/evolva-molecular-slm with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Pippinlitli/evolva-molecular-slm
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "Pippinlitli/evolva-molecular-slm" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Pippinlitli/evolva-molecular-slm with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Pippinlitli/evolva-molecular-slm
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default Pippinlitli/evolva-molecular-slm
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use Pippinlitli/evolva-molecular-slm with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Pippinlitli/evolva-molecular-slm
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "Pippinlitli/evolva-molecular-slm" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
- Docker Model Runner
How to use Pippinlitli/evolva-molecular-slm with Docker Model Runner:
docker model run hf.co/Pippinlitli/evolva-molecular-slm
- Lemonade
How to use Pippinlitli/evolva-molecular-slm with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Pippinlitli/evolva-molecular-slm
Run and chat with the model
lemonade run user.evolva-molecular-slm-{{QUANT_TAG}}List all available models
lemonade list
Evolva Molecular SLM
Evolva is a genetic-validated drug discovery platform powered by a Small Language Model (SLM) trained on curated molecular datasets. It predicts pIC50 values, validates drug targets, synthesizes reaction routes, and identifies patent workarounds.
Model Description
The Evolva Molecular SLM is a domain-specific language model fine-tuned on:
- ChEMBL bioactivity data (pIC50 values)
- SMILES molecular representations
- Target-ligand interaction data
- Reaction pathway databases
Capabilities
| Task | Description |
|---|---|
| pIC50 Prediction | Predict binding affinity from SMILES input |
| Target Validation | Validate genetic drug targets |
| Route Synthesis | Generate synthetic reaction pathways |
| Patent Workaround | Identify non-infringing molecular variants |
Usage
from huggingface_hub import hf_hub_download
# Model will be available after Sprint 46 training completes
model_path = hf_hub_download(
repo_id="Pippinlitli/evolva-molecular-slm",
filename="model.gguf"
)
Inference API
Live predictions available at: https://huggingface.co/spaces/Pippinlitli/evolva-inference
Demo UI
Interactive Gradio demo: https://huggingface.co/spaces/Pippinlitli/evolva-frontend
Status
Note: The
model.gguffile will be uploaded after Sprint 46 training completes. The inference API currently returns a graceful error message until the model is available.
Citation
@misc{evolva2026,
title={Evolva: Genetic-Validated Drug Discovery via Molecular SLM},
author={Gudmundur Eyberg Kristjansson},
year={2026},
url={https://huggingface.co/Pippinlitli/evolva-molecular-slm}
}
License
Apache 2.0
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