Instructions to use Tuguberk/Qwen3.5-2B-Turkish-SFT-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Tuguberk/Qwen3.5-2B-Turkish-SFT-LoRA with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Tuguberk/Qwen3.5-2B-Turkish-SFT-LoRA")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Tuguberk/Qwen3.5-2B-Turkish-SFT-LoRA", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Tuguberk/Qwen3.5-2B-Turkish-SFT-LoRA with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Tuguberk/Qwen3.5-2B-Turkish-SFT-LoRA"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Tuguberk/Qwen3.5-2B-Turkish-SFT-LoRA",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Tuguberk/Qwen3.5-2B-Turkish-SFT-LoRA

SGLang

How to use Tuguberk/Qwen3.5-2B-Turkish-SFT-LoRA with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Tuguberk/Qwen3.5-2B-Turkish-SFT-LoRA" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Tuguberk/Qwen3.5-2B-Turkish-SFT-LoRA",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Tuguberk/Qwen3.5-2B-Turkish-SFT-LoRA" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Tuguberk/Qwen3.5-2B-Turkish-SFT-LoRA",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio

How to use Tuguberk/Qwen3.5-2B-Turkish-SFT-LoRA with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Tuguberk/Qwen3.5-2B-Turkish-SFT-LoRA to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Tuguberk/Qwen3.5-2B-Turkish-SFT-LoRA to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Tuguberk/Qwen3.5-2B-Turkish-SFT-LoRA to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="Tuguberk/Qwen3.5-2B-Turkish-SFT-LoRA",
    max_seq_length=2048,
)

Docker Model Runner
How to use Tuguberk/Qwen3.5-2B-Turkish-SFT-LoRA with Docker Model Runner:
```
docker model run hf.co/Tuguberk/Qwen3.5-2B-Turkish-SFT-LoRA
```

Qwen3.5-2B-Turkish-SFT — LoRA Adaptörleri

Bu repo, Tuguberk/Qwen3.5-2B-Turkish-SFT modelinin sadece LoRA adaptörlerini içerir. Merged (birleştirilmiş) modeli kullanmak istiyorsanız ana repoya gidin.

LoRA nedir?

LoRA (Low-Rank Adaptation), modelin tüm ağırlıklarını değiştirmek yerine küçük adaptör katmanları ekleyerek fine-tuning yapan bir yöntemdir. Bu repo sadece o adaptörleri (~100MB) içerir — base modeli ayrıca indirmeniz gerekir.

Adaptör Detayları


Base model	unsloth/Qwen3.5-2B
LoRA rank	16
LoRA alpha	16
Target modules	q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
Eğitilebilir parametre	16,819,200 / 2,230,060,864 (%0.75)
Dataset	AlicanKiraz0/Turkish-SFT-Dataset-v1.0
Epoch	3
Training loss	1.47 → 0.82

Kullanım

from transformers import AutoModelForCausalLM, AutoProcessor
from peft import PeftModel
import torch

base_model_name  = "unsloth/Qwen3.5-2B"
lora_model_name  = "Tuguberk/Qwen3.5-2B-Turkish-SFT-LoRA"

# Base modeli yükle
processor = AutoProcessor.from_pretrained(base_model_name)
tokenizer = processor.tokenizer

model = AutoModelForCausalLM.from_pretrained(
    base_model_name,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)

# LoRA adaptörlerini üstüne ekle
model = PeftModel.from_pretrained(model, lora_model_name)
model.eval()

# Kullanım
messages = [
    {"role": "system", "content": "Sen yardımcı bir Türkçe asistansın."},
    {"role": "user",   "content": "Yapay zeka nedir?"},
]

text = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True,
    enable_thinking=False,
)
inputs = tokenizer(text, return_tensors="pt").to(model.device)

outputs = model.generate(
    inputs["input_ids"],
    max_new_tokens=512,
    temperature=0.7,
    top_p=0.9,
    do_sample=True,
)

response = tokenizer.decode(outputs[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True)
print(response)

Ne zaman LoRA, ne zaman merged model kullanılır?

	LoRA (bu repo)	Merged model
Dosya boyutu	~100MB	~4.5GB
Base model gerekli mi?	✅ Evet	❌ Hayır
Ollama / llama.cpp	❌ Çalışmaz	✅ Çalışır
Araştırma / deney	✅ İdeal	—
Production kullanım	—	✅ İdeal

Çoğu kullanım için merged modeli tercih edin: Tuguberk/Qwen3.5-2B-Turkish-SFT

Lisans

Apache 2.0 — base model lisansıyla aynıdır.

Downloads last month: -; Downloads are not tracked for this model. How to track

Model tree for Tuguberk/Qwen3.5-2B-Turkish-SFT-LoRA

Base model

Qwen/Qwen3.5-2B-Base

Finetuned

Qwen/Qwen3.5-2B

Finetuned

unsloth/Qwen3.5-2B

Adapter

(26)

this model

Tuguberk
/

Qwen3.5-2B-Turkish-SFT-LoRA