Instructions to use Pippinlitli/evolva-molecular-slm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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

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.gguf file 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

Downloads last month: 9

GGUF

Model size

2B params

Architecture

qwen2

Hardware compatibility

We're not able to determine the quantization variants.

View all variants

Pippinlitli
/

evolva-molecular-slm

Evolva Molecular SLM

Model Description

Capabilities

Usage

Inference API

Demo UI

Status

Citation

License

Spaces using Pippinlitli/evolva-molecular-slm 4