Downloads · 30 days
8
36% of all-time downloads
Gemma-2b-It_EU-AI-Reglementation
ApyHTML19/Gemma-2b-It_EU-AI-Reglementation
Gemma-2b-It_EU-AI-Reglementation is a machine learning model from ApyHTML19. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
This model is a fine-tuned version of google/gemma-2b-it using LoRA (Low-Rank Adaptation) on a custom instruction dataset.
All-time downloads
22
Public
Parameters
2.5B
3.1 GB on disk
Likes
1
Public
Repo makeup
Click a slice to open those files.
.safetensors3.1 GB · 99%
Parameter types
How the weights are stored.
U82B · 79%
Model card
From the Hugging Face model README
🧠 Gemma-2B-IT LoRA Fine-Tuned
This model is a fine-tuned version of google/gemma-2b-it using LoRA (Low-Rank Adaptation) on a custom instruction dataset.
Model Details
- Base model: google/gemma-2b-it
- Fine-tuning method: LoRA (PEFT)
- Quantization: 4-bit (NF4) during training
- Framework: HuggingFace Transformers + TRL + PEFT
- Hardware: NVIDIA GPU /AWS)
Training Details
| Parameter | Value |
|---|---|
| LoRA rank (r) | 8 |
| LoRA alpha | 16 |
| LoRA dropout | 0.05 |
| Target modules | q_proj, k_proj, v_proj, o_proj |
| Learning rate | 2e-4 |
| Epochs | 3 |
| Batch size | 1 |
| Gradient accumulation | 16 steps |
| Optimizer | paged_adamw_8bit |
| Max sequence length | 256 |
Usage
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel
import torch
base_model = "google/gemma-2b-it"
adapter = "your-username/your-repo-name"
tokenizer = AutoTokenizer.from_pretrained(base_model)
model = AutoModelForCausalLM.from_pretrained(
base_model,
torch_dtype=torch.float16,
device_map="auto"
)
model = PeftModel.from_pretrained(model, adapter)
prompt = "<start_of_turn>user\nYour question here<end_of_turn>\n<start_of_turn>model\n"
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=200)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
Dataset Format
The model was trained on instruction/response pairs in the following format: https://huggingface.co/datasets/ApyHTML19/EU-AI-Regulation-GDPR-2025
- Type
- gemma
- License
- mit
- Created
- Aug 29, 2026
- Updated
- Aug 29, 2026