Instructions to use gpsworld8800/onomastics with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use gpsworld8800/onomastics with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="gpsworld8800/onomastics",
	filename="onomastics.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use gpsworld8800/onomastics with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf gpsworld8800/onomastics
# Run inference directly in the terminal:
llama-cli -hf gpsworld8800/onomastics

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf gpsworld8800/onomastics
# Run inference directly in the terminal:
llama-cli -hf gpsworld8800/onomastics

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 gpsworld8800/onomastics
# Run inference directly in the terminal:
./llama-cli -hf gpsworld8800/onomastics

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 gpsworld8800/onomastics
# Run inference directly in the terminal:
./build/bin/llama-cli -hf gpsworld8800/onomastics

Use Docker

docker model run hf.co/gpsworld8800/onomastics

LM Studio
Jan
Ollama
How to use gpsworld8800/onomastics with Ollama:
```
ollama run hf.co/gpsworld8800/onomastics
```

Unsloth Studio new

How to use gpsworld8800/onomastics 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 gpsworld8800/onomastics 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 gpsworld8800/onomastics to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for gpsworld8800/onomastics to start chatting

Pi new

How to use gpsworld8800/onomastics with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf gpsworld8800/onomastics

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": "gpsworld8800/onomastics"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use gpsworld8800/onomastics with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf gpsworld8800/onomastics

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 gpsworld8800/onomastics

Run Hermes

hermes

Docker Model Runner
How to use gpsworld8800/onomastics with Docker Model Runner:
```
docker model run hf.co/gpsworld8800/onomastics
```

Lemonade

How to use gpsworld8800/onomastics with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull gpsworld8800/onomastics

Run and chat with the model

lemonade run user.onomastics-{{QUANT_TAG}}

List all available models

lemonade list

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🧾 Model Card: your-model-name

📌 Model Details

Developed by: gpsworld8800
Model type: Large Language Model
Architecture: LLaMA
Language(s): English / Hindi / Multilingual
License: Apache 2.0

🛠️ Intended Uses

Predicting religion/ethnicity from Indian names
Research on Indian onomastics & linguistics
Educational or demo purposes

⚠️ Not intended for:

Making decisions in sensitive contexts (hiring, loans, etc.)
Any discriminatory use

🧑‍💻 How to Use

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("gpsworld8800/onomastics")
model = AutoModelForCausalLM.from_pretrained("gpsworld8800/onomastics")

inputs = tokenizer("Prathamesh Gate", return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=20)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Downloads last month: -

GGUF

Model size

8B params

Architecture

llama

Hardware compatibility

We're not able to determine the quantization variants.

View all variants

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Evaluation results

accuracy on custom-dataset
self-reported

0.920