---
base_model: LiquidAI/LFM2-350M
library_name: transformers
pipeline_tag: text-generation
tags:
- lfm2
- peft
- portfolio-assistant
- grounded-generation
license: other
license_name: lfm1.0
license_link: https://huggingface.co/LiquidAI/LFM2-350M/blob/main/LICENSE
---

# Daniel OS LFM2-350M

Personalized LFM2-350M checkpoint for Sangbum Daniel Choi's browser-native
portfolio assistant. The model was adapted with LoRA and merged for deployment.

## Scope behavior

The training set contains 296 curated conversations:

- Verified-profile answers: 177
- Evidence-grounded definitions: 12
- Public-retrieval decisions: 15
- Explicitly missing profile facts: 58
- Privacy and safety refusals: 34

Training data revision: `e54fa0460fd6e2e3c4c077607bfb79184d94fbdb`

The assistant is trained to separate Daniel-specific claims from general
definitions. It synthesizes definitions only from retrieved evidence, emits a
public-search tool request when evidence is missing, and never claims to be Daniel.

## Held-out behavioral evaluation

- Overall: 84.4%
- Verified-profile answers: 81.8%
- Evidence-grounded definitions: 100.0%
- Retrieval decisions: 75.0%
- Missing-profile facts: 75.0%
- Privacy and safety refusals: 100.0%

The website supplies focused verified profile context and recent conversation
history to this model. Privacy boundaries, visitor-identity handling, career
chronology, and contextual follow-up behavior are learned from the SFT data
rather than returned as fixed JavaScript answers.