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pramod-thaz/finance-cre-finetuned
finance-cre-finetuned is a machine learning model from pramod-thaz. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Fine-tuned Phi-3.5-mini model for Commercial Real Estate (CRE) & Finance/Economics domain knowledge, built upon Microsoft Phi 3.5 mini.
Downloads · 30 days
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4% of all-time downloads
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.gguf2.4 GB · 100%
From the Hugging Face model README
Fine-tuned Phi-3.5-mini model for Commercial Real Estate (CRE) & Finance/Economics domain knowledge, built upon Microsoft Phi 3.5 mini.
| Attribute | Value |
|---|---|
| Base Model | microsoft/Phi-3.5-mini-instruct |
| Parameters | 3.8B |
| Quantization | Q4_K_M (~2.2 GB) |
| Context Length | 2048 tokens |
This model specializes in Commercial Real Estate terminology and concepts across all major asset classes.
Trained on 658 Q&A pairs covering:
# Run directly from HuggingFace (no download needed)
ollama run hf.co/pramod-thaz/finance-cre-finetuned
# Or pull locally first
ollama pull pramod-thaz/finance-cre-finetuned
ollama run finance-cre-finetuned
# Download GGUF and run with llama.cpp
./llama-cli -m finance-cre-finetuned-v0.1-Q4_K_M.gguf -n 256 --temp 0.3
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "pramod-thaz/finance-cre-finetuned"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
| Version | Date | Notes |
|---|---|---|
| v0.1 | April 2026 | Initial release - 658 training pairs |
This model is fine-tuned for educational and informational purposes. For actual investment decisions, consult with qualified professionals.
Fine-tuned Phi-3.5-mini for Commercial Real Estate
https://huggingface.co/pramod-thaz/finance-cre-finetuned
This model is based on Phi-3.5-mini which uses the MIT License. Check individual model cards for specific licensing information.
Note: This is v0.1 - a foundational model. Future versions will include more training data and improved accuracy on CRE-specific terminology.