| ---
|
| license: apache-2.0
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| base_model: LiquidAI/LFM2.5-1.2B-Instruct
|
| tags:
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| - homie
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| - personal-assistant
|
| - fine-tuned
|
| - local-first
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| - privacy
|
| - tool-use
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| pipeline_tag: text-generation
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| language:
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| - en
|
| ---
|
|
|
| # Homie -- Personal AI Assistant
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|
|
| Homie is a privacy-first, local AI assistant with identity baked into the weights.
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| No system prompt needed. The model inherently knows it's Homie.
|
|
|
| ## Features
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| - Identity: Knows it's Homie, not a generic chatbot
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| - Tool-aware: Understands email, calendar, files, git, web search, voice, mesh
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| - Privacy-first: Emphasizes local-only, no cloud
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| - Concise: Leads with answers, code-first for dev questions
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| - Secure: Refuses prompt injection, never leaks credentials
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| - Multi-device: Understands mesh networking and device sync
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| - Learning: Remembers preferences across sessions
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|
|
| ## Training
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| - Base model: LiquidAI/LFM2.5-1.2B-Instruct (Apache 2.0)
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| - Method: QLoRA (rank 64, alpha 128, 0.54% trainable)
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| - Data: 69 hand-crafted examples across 10 categories (x3 = 207 total)
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| - DPO: 10 preference pairs (Homie-style vs generic)
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| - Categories: identity, tools, mesh, memory, security, coding, proactive, errors, flow, system
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| - Epochs: 5, Loss: 1.414, Accuracy: 92%
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|
|
| ## Usage
|
|
|
| ```python
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| from transformers import AutoModelForCausalLM, AutoTokenizer
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|
|
| model = AutoModelForCausalLM.from_pretrained("Muthu88/Homie", trust_remote_code=True)
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| tokenizer = AutoTokenizer.from_pretrained("Muthu88/Homie", trust_remote_code=True)
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|
|
| messages = [{"role": "user", "content": "Who are you?"}]
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| text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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| inputs = tokenizer(text, return_tensors="pt").to(model.device)
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| output = model.generate(**inputs, max_new_tokens=100)
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| print(tokenizer.decode(output[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True))
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| ```
|
|
|
| ## Part of the Homie AI Project
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| - GitHub: https://github.com/MSG-88/Homie
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| - Website: https://heyhomie.app
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|
|
