prawinn04/vensa-1.1b-gguf

🛸 Vensa 1.1B (GGUF)

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Vensa 1.1B is a lightweight, specialized AI model fine-tuned for Flutter Development and Dart Programming.

This GGUF version is optimized for high-performance inference on local machines and edge devices using llama.cpp. It balances a small footprint with deep knowledge of mobile app architecture and widget implementation.

👤 Developer Information

• Developer: Praveen Kumar
• Portfolio: praveen-dev.space
• Contact: praveenvenkat042k@gmail.com
• Expertise: Flutter Development, AI Engineering, and Server Configurations

🛠 Model Details

• Architecture: Llama-based (1.1B Parameters)
• Format: GGUF (Optimized for CPU & Mobile)
• Quantization: Q4_K_M (High efficiency with minimal quality loss)
• Primary Focus: Dart syntax, Flutter widget trees, state management (Provider, Riverpod, Bloc), and mobile UI/UX patterns

🔒 API Implementation

While the model weights are open-source (GGUF), the Vensa API is currently a private service used for specialized integrations.

If you are interested in collaboration or custom API access, please contact the developer directly.

💻 How to Use (Python / llama-cpp-python)

To run this model locally, first install the dependencies:

pip install llama-cpp-python huggingface-hub
Then run the following Python script:

Python

from llama_cpp import Llama
from huggingface_hub import hf_hub_download

# 1. Download the GGUF model
model_path = hf_hub_download(
    repo_id="prawinn04/vensa-1.1b-gguf",
    filename="vensa-1.1b.gguf"
)

# 2. Load the model
llm = Llama(
    model_path=model_path,
    n_ctx=2048,
    n_threads=4  # Adjust based on your CPU cores
)

# 3. Run a Flutter-related prompt
output = llm(
    "### Instruction:\nExplain how to use a ListView.builder in Flutter.\n\n### Response:",
    max_tokens=512,
    stop=["### Instruction:"]
)

print(output['choices'][0]['text'])
⚖️ License
This model is released under the MIT License.