Instructions to use georgebu/dpo_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use georgebu/dpo_model with Transformers:

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

pipe = pipeline("text-generation", model="georgebu/dpo_model")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("georgebu/dpo_model")
model = AutoModelForCausalLM.from_pretrained("georgebu/dpo_model")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use georgebu/dpo_model with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/georgebu/dpo_model

SGLang

How to use georgebu/dpo_model 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 "georgebu/dpo_model" \
    --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": "georgebu/dpo_model",
		"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 "georgebu/dpo_model" \
        --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": "georgebu/dpo_model",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use georgebu/dpo_model with Docker Model Runner:
```
docker model run hf.co/georgebu/dpo_model
```

Описание модели

В рамках домашнего задания по курсу "Современный NLP. Большие языковые модели" от vk.education было реализовано дообучение модели методом Direct Preference Optimization (DPO)

Как использовать:

tokenizer = AutoTokenizer.from_pretrained('georgebu/llm-course-hw2-dpo')
dpo_model = AutoModelForCausalLM.from_pretrained(georgebu/llm-course-hw2-dpo)

messages = [{"role": "user", "content": "What's your morning routine like?"}]

text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
model_inputs = tokenizer([text], return_tensors="pt").to(device)

generated_ids = dpo_model.generate(model_inputs.input_ids, max_new_tokens=256, do_sample=False)
response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
print(response)

Примеры генерации:

Промт: "What is your morning routine like?"

Ответ модели:
I'm excited to help you with your morning routine. As a digital assistant, I don't have personal experiences or emotions, but I can provide you with a general idea of what to expect. Please feel free to adjust the content to fit your needs.
Morning Routine (10-15 minutes)
Get Ready:Wash your face with soap and water.
Apply a facial wash or moisturizer.
Use a gentle cleanser.
Massage the cleanser into your skin.

Brush and Towel:Brush your teeth with a soft-bristled toothbrush.
Use a gentle circular motion.
Rinse with warm water.

Get Ready:Put on your favorite outfit.
Choose a comfortable and outfit.
Remove any shoes.