You can deploy this model and start earning money today!

oriolrius/
phi3-avro-gguf-q4km

Name: phi3-avro-gguf-q4km
Availability: InStock

oriolrius/avro-schema-examples

microsoft/Phi-3-mini-4k-instruct

quantized

mit

endpoints_compatible

Views

No views yet

Phi-3 Mini 4K AVRO Fine-tuned Model (Ollama)

This is a fine-tuned version of Microsoft's Phi-3 Mini 4K model, specifically trained on AVRO-related tasks and exported for use with Ollama.

Model Details

Base Model: Microsoft Phi-3 Mini 4K
Fine-tuning: LoRA with rank 32, alpha 64, 20 epochs
Export Format: GGUF (Quantized q4_k_m)
Export Date: 2025-09-15
Export Tool: Docker-based Ollama export
Model Size: ~7.2GB (quantized)

Files

model.gguf: The quantized model file in GGUF format
Modelfile: Ollama configuration file with model parameters
docker-compose.yml: Docker setup for running the model
setup_ollama.sh: Script to set up Ollama with this model
test_model.sh: Script to test the model functionality

Usage

With Ollama

Download the model files
Run the setup script:

bash
1chmod +x setup_ollama.sh 2./setup_ollama.sh
Use the model:

ollama run phi3-avro

With Docker Compose

docker-compose up -d

Model Parameters

Temperature: 0.7
Top-p: 0.9
Top-k: 40
Max tokens: 2048

Fine-tuning Details

This model was fine-tuned using LoRA (Low-Rank Adaptation) technique:

Rank: 32
Alpha: 64
Training epochs: 20
Training completed: 2025-09-14

The model has been specifically trained to understand and work with AVRO schemas, data serialization, and related data engineering tasks.

License

This model inherits the license from the base Phi-3 Mini model. Please refer to Microsoft's Phi-3 licensing terms.

Technical Specifications

Quantization: q4_k_m (4-bit quantization with k-means)
Context length: 4096 tokens
Export method: Docker container compilation
Compatible with: Ollama, llama.cpp ecosystem

oriolrius/phi3-avro-gguf-q4km