Instructions to use AI-Sweden-Models/Llama-3-8B-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AI-Sweden-Models/Llama-3-8B-instruct with Transformers:

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

pipe = pipeline("text-generation", model="AI-Sweden-Models/Llama-3-8B-instruct")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("AI-Sweden-Models/Llama-3-8B-instruct")
model = AutoModelForCausalLM.from_pretrained("AI-Sweden-Models/Llama-3-8B-instruct")
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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use AI-Sweden-Models/Llama-3-8B-instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "AI-Sweden-Models/Llama-3-8B-instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AI-Sweden-Models/Llama-3-8B-instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/AI-Sweden-Models/Llama-3-8B-instruct

SGLang

How to use AI-Sweden-Models/Llama-3-8B-instruct 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 "AI-Sweden-Models/Llama-3-8B-instruct" \
    --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": "AI-Sweden-Models/Llama-3-8B-instruct",
		"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 "AI-Sweden-Models/Llama-3-8B-instruct" \
        --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": "AI-Sweden-Models/Llama-3-8B-instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use AI-Sweden-Models/Llama-3-8B-instruct with Docker Model Runner:
```
docker model run hf.co/AI-Sweden-Models/Llama-3-8B-instruct
```

Finetuning datasets used?

by saattrupdan - opened Nov 30, 2024

Discussion

saattrupdan

Nov 30, 2024

Your model is performing extraordinarily good at ScandEval, way better than your AI-Sweden-Models/Llama-3-8B base model, so I'm a bit concerned that there's been some data leakage. It's hard to check since you haven't stated which datasets you used for finetuning, but perhaps you know if any of the ScandEval datasets were used?

The datasets in question are (at least) the following:

🇸🇪 SUC 3.0
🇸🇪 ScaLA-sv
🇸🇪 MMLU-sv
🇸🇪 HellaSwag-sv
🇩🇰 DANSK
🇩🇰 Angry Tweets
🇩🇰 ScaLA-da
🇩🇰 HellaSwag-da

I've also emailed 42labs about the same question, see if they can shed some light on it.

timpal0l

AI Sweden Model Hub org Dec 9, 2024

•

edited Dec 9, 2024

@saattrupdan Its only been trained on Swedish, so the great scores in Norweigian and Danish would be transfered, impossible to be a leak. https://huggingface.co/four-two-labs/lynx-micro#training-data (would be the same dataset). Did you get any more information from 42? Did you remove this model from ScandEval?

saattrupdan

Dec 9, 2024

Hey @timpal0l .

I removed it from ScandEval temporarily, while the question about the dataset was pending. I've added it back in now, now that it's clarified :)

Heard back from Ali as well, and he also reassured me that there was no leak, but could not say much about the dataset itself, due to its proprietary nature.

saattrupdan changed discussion status to closed Dec 9, 2024

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