Instructions to use abhishek040404/v2f-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use abhishek040404/v2f-gguf with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="abhishek040404/v2f-gguf",
	filename="farmai-q4km.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 abhishek040404/v2f-gguf with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf abhishek040404/v2f-gguf
# Run inference directly in the terminal:
llama-cli -hf abhishek040404/v2f-gguf

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf abhishek040404/v2f-gguf
# Run inference directly in the terminal:
llama-cli -hf abhishek040404/v2f-gguf

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 abhishek040404/v2f-gguf
# Run inference directly in the terminal:
./llama-cli -hf abhishek040404/v2f-gguf

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 abhishek040404/v2f-gguf
# Run inference directly in the terminal:
./build/bin/llama-cli -hf abhishek040404/v2f-gguf

Use Docker

docker model run hf.co/abhishek040404/v2f-gguf

LM Studio
Jan
Ollama
How to use abhishek040404/v2f-gguf with Ollama:
```
ollama run hf.co/abhishek040404/v2f-gguf
```

Unsloth Studio new

How to use abhishek040404/v2f-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 abhishek040404/v2f-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 abhishek040404/v2f-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for abhishek040404/v2f-gguf to start chatting

Pi new

How to use abhishek040404/v2f-gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf abhishek040404/v2f-gguf

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": "abhishek040404/v2f-gguf"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use abhishek040404/v2f-gguf with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf abhishek040404/v2f-gguf

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 abhishek040404/v2f-gguf

Run Hermes

hermes

Docker Model Runner
How to use abhishek040404/v2f-gguf with Docker Model Runner:
```
docker model run hf.co/abhishek040404/v2f-gguf
```

Lemonade

How to use abhishek040404/v2f-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull abhishek040404/v2f-gguf

Run and chat with the model

lemonade run user.v2f-gguf-{{QUANT_TAG}}

List all available models

lemonade list

FarmAI — GGUF (Q4_K_M) | Multilingual Agricultural AI

Fine-tuned Qwen2.5-3B converted to GGUF for Ollama. Understands: English, Hindi, Hinglish, Telugu-English, Kannada-English.

Run with Ollama

# Download Modelfile from this repo, then:
ollama create farmai -f Modelfile
ollama run farmai

Ask in any language: meri buffalo ka doodh kam ho gaya or నా buffalo పాలు తక్కువగా ఉన్నాయి

Domain: Agriculture, Dairy, Organic Farming, Government Schemes
Knowledge: 548 verified agricultural facts
Size: ~2 GB (Q4_K_M quantization)

Downloads last month: 1

GGUF

Model size

3B params

Architecture

qwen2

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

Model tree for abhishek040404/v2f-gguf

Base model

abhishek040404/qwen_model_M

Quantized

(1)

this model