ReallyFloppyPenguin/Nanonets-OCR-s-GGUF

nanonets/Nanonets-OCR-s - GGUF

This repository contains GGUF quantizations of nanonets/Nanonets-OCR-s.

About GGUF

GGUF is a quantization method that allows you to run large language models on consumer hardware by reducing the precision of the model weights.

Files

Filename	Quant type	File Size	Description
model-f16.gguf	f16	Large	Original precision
model-q4_0.gguf	Q4_0	Small	4-bit quantization
model-q4_1.gguf	Q4_1	Small	4-bit quantization (higher quality)
model-q5_0.gguf	Q5_0	Medium	5-bit quantization
model-q5_1.gguf	Q5_1	Medium	5-bit quantization (higher quality)
model-q8_0.gguf	Q8_0	Large	8-bit quantization

Usage

You can use these models with llama.cpp or any other GGUF-compatible inference engine.

llama.cpp

./llama-cli -m model-q4_0.gguf -p "Your prompt here"

Python (using llama-cpp-python)

from llama_cpp import Llama

llm = Llama(model_path="model-q4_0.gguf")
output = llm("Your prompt here", max_tokens=512)
print(output['choices'][0]['text'])

Original Model

This is a quantized version of nanonets/Nanonets-OCR-s. Please refer to the original model card for more information about the model's capabilities, training data, and usage guidelines.

Conversion Details

• Converted using llama.cpp
• Original model downloaded from Hugging Face
• Multiple quantization levels provided for different use cases

License

This model inherits the license from the original model. Please check the original model's license for usage terms.