How to use from
Hermes Agent
Start the llama.cpp server
# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf mahmoudd777/qwen35-realestate-2048:Q4_K_M
Configure Hermes
# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default mahmoudd777/qwen35-realestate-2048:Q4_K_M
Run Hermes
hermes
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Qwen3.5-4B โ€” Real Estate Call Analysis (Egyptian Market)

Fine-tuned version of Qwen3.5-4B for extracting structured information from real estate call transcripts in the Egyptian market. Supports English and Egyptian Arabic.

What it does

Given a call transcript, the model extracts a structured JSON object with:

  • Client name, sentiment, urgency, timeline
  • Confidence score and transcript quality score
  • Client profile, special requests, action items, call summary
  • requested_units array with: intent, property type, location, currency, budget, payment method, area, bedrooms, finishing, key objection

Training

  • Base model: Qwen/Qwen3.5-4B
  • Method: LoRA fine-tuning (r=16) via Unsloth
  • Dataset: 650 real estate call transcripts (70% English, 30% Egyptian Arabic)
  • Sequence length: 2048 tokens
  • Epochs: 6

Language support

  • English call transcripts
  • Egyptian Arabic call transcripts
  • Mixed Arabic/English conversations
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Model size
4B params
Architecture
qwen35
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