AYI-NEDJIMI/ISO27001-Expert-1.5B-Merged

ISO27001-Expert-1.5B — Merged (Standalone)

Expert en norme ISO 27001 (Systemes de Management de la Securite de l'Information)

This is the merged / standalone version of AYI-NEDJIMI/ISO27001-Expert-1.5B. The LoRA adapter weights have been fully merged into the base model (Qwen/Qwen2.5-1.5B-Instruct), so no PEFT library is required at inference time.

Description

• —FR : Expert en norme ISO 27001 (Systemes de Management de la Securite de l'Information). Version fusionnee — chargement direct sans adaptateur PEFT.
• —EN : ISO 27001 Information Security Management Systems expert. Merged version — direct loading without PEFT adapter.

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "AYI-NEDJIMI/ISO27001-Expert-1.5B-Merged"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype="auto",
    device_map="auto",
)

messages = [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "Explain the key principles of ISO 27001."},
]

text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(text, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Note: No need to install or import peft — this model is fully standalone.

Links

• —Adapter version (LoRA): AYI-NEDJIMI/ISO27001-Expert-1.5B
• —Base model: Qwen/Qwen2.5-1.5B-Instruct
• —Portfolio collection: AYI-NEDJIMI Collections

Training details

This model was fine-tuned using LoRA (Low-Rank Adaptation) with the following configuration:

• —LoRA rank (r): 64
• —LoRA alpha: 128
• —LoRA dropout: 0.05
• —Target modules: qproj, kproj, vproj, oproj, gateproj, upproj, down_proj

The adapter weights were then merged into the base model using model.merge_and_unload() from the PEFT library to produce this standalone checkpoint.