|
|
--- |
|
|
base_model: |
|
|
- inference-net/Schematron-3B |
|
|
pipeline_tag: text-generation |
|
|
tags: |
|
|
- open4bits |
|
|
license: llama3.2 |
|
|
--- |
|
|
# Open4bits / Schematron-3B-GGUF |
|
|
|
|
|
This repository provides the **Schematron-3B model converted to GGUF format**, published by Open4bits to enable efficient local inference with reduced memory usage and broad CPU compatibility. |
|
|
|
|
|
The underlying base model is **meta-llama/Llama-3.2-3B-Instruct**, fine-tuned by Inference-Net. This repository contains a quantized GGUF conversion of the fine-tuned model weights produced by Open4bits. |
|
|
|
|
|
The model is designed for instruction-based text generation tasks and is suitable for resource-constrained and local deployments. |
|
|
|
|
|
--- |
|
|
|
|
|
## Model Overview |
|
|
|
|
|
Schematron-3B is an instruction-tuned language model built on the **LLaMA 3.2-3B architecture**. After fine-tuning by Inference-Net for enhanced instruction following and generation quality, the model has been quantized and released in GGUF format to support efficient CPU-friendly inference. |
|
|
|
|
|
--- |
|
|
|
|
|
## Model Details |
|
|
|
|
|
* **Base Model:** meta-llama/Llama-3.2-3B-Instruct |
|
|
* **Fine-Tuned By:** Inference-Net |
|
|
* **Parameters:** ~3 billion |
|
|
* **Format:** GGUF (quantized) |
|
|
* **Task:** Instruction-based text generation |
|
|
* **Weight tying:** Preserved |
|
|
* **Compatibility:** GGUF-compatible inference engines and CPU environments |
|
|
|
|
|
This quantized release is designed to balance performance and resource efficiency while maintaining strong instruction following capabilities. |
|
|
|
|
|
--- |
|
|
|
|
|
## Intended Use |
|
|
|
|
|
This model is intended for: |
|
|
|
|
|
* Instruction-guided text generation |
|
|
* Local and CPU-based inference workflows |
|
|
* Research, prototyping, and experimentation |
|
|
* Self-hosted or offline AI systems |
|
|
|
|
|
--- |
|
|
|
|
|
## Limitations |
|
|
|
|
|
* Reduced generation quality compared to larger or full-precision variants |
|
|
* Performance depends on prompt design and inference parameters |
|
|
* Not fine-tuned for highly specialized or domain-specific tasks |
|
|
|
|
|
--- |
|
|
|
|
|
## License |
|
|
|
|
|
This model follows the **original LLaMA 3.2 licensing terms** as defined by Meta AI. |
|
|
Users must comply with the licensing conditions of the base model and the fine-tuning provider. |
|
|
|
|
|
--- |
|
|
|
|
|
## Support |
|
|
|
|
|
If you find this model valuable, please consider supporting the project. |
|
|
Your support helps Open4bits continue releasing and maintaining high-quality quantized models for the community. |
