Parameter	Value
Base model	`TinyLlama/TinyLlama-1.1B-Chat-v1.0`
Method	LoRA (PEFT) — merged into full weights
LoRA rank (r)	16
LoRA alpha	32
LoRA dropout	0.05
Target modules	q_proj, k_proj, v_proj, o_proj
Epochs	2
Training steps	30
Final train loss	1.3873
Dataset	ShareGPT format, domain-specific ESP32 examples
GPU	Quadro P2000 (5 GB VRAM)
Framework	Hugging Face Transformers + PEFT

Usage

python

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("electron-rare/mascarade-esp32")
tokenizer = AutoTokenizer.from_pretrained("electron-rare/mascarade-esp32")

messages = [{"role": "user", "content": "How do I configure deep sleep on ESP32-S3?"}]
inputs = tokenizer.apply_chat_template(messages, return_tensors="pt")
outputs = model.generate(inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Related models

Model	Domain	Base
mascarade-iot	IoT general	Qwen2.5-Coder-1.5B
mascarade-spice	SPICE circuit simulation	TinyLlama-1.1B
mascarade-platformio	PlatformIO development	TinyLlama-1.1B

Datasets

All training datasets are available under clemsail on Hugging Face.

🇪🇺 EU AI Act transparency

This adapter is provided as a fine-tuned LoRA under the AI Act framework (Regulation EU 2024/1689). Compliance metadata:

Field	Value
Provider	L'Électron Rare (clemsail / electron-rare)
Role under AI Act	GPAI provider for this adapter
Base model	`TinyLlama/TinyLlama-1.1B-Chat-v1.0` — see upstream provenance
Adapter type	LoRA / PEFT — adapter weights only; base unchanged
Training data origin	L'Électron Rare proprietary technical corpus + curated public docs
License	Apache-2.0 (adapter). Upstream base licence applies separately.
Intended use	ESP32 / ESP-IDF firmware
Out of scope	Healthcare diagnosis, legal advice, autonomous safety-critical decisions, generation of malicious code
Risk classification	Limited risk — Article 50 transparency obligations apply
Copyright respect	Training data does not include scraped copyrighted material. Opt-out signals (robots.txt, ai.txt) are honoured for web-sourced data.
Full provenance	https://github.com/ailiance/ailiance/tree/main/docs/provenance
Contact	postmaster@saillant.cc — biased output reports, copyright concerns, etc.

⚠️ You are using an AI model. Outputs may be inaccurate, biased or fabricated. Do not act on them without independent verification, especially in regulated domains.