Instructions to use four-two-labs/lynx-micro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use four-two-labs/lynx-micro with Transformers:

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

pipe = pipeline("text-generation", model="four-two-labs/lynx-micro")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("four-two-labs/lynx-micro")
model = AutoModelForCausalLM.from_pretrained("four-two-labs/lynx-micro", device_map="auto")
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 Settings

vLLM

How to use four-two-labs/lynx-micro with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/four-two-labs/lynx-micro

SGLang

How to use four-two-labs/lynx-micro 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 "four-two-labs/lynx-micro" \
    --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": "four-two-labs/lynx-micro",
		"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 "four-two-labs/lynx-micro" \
        --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": "four-two-labs/lynx-micro",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use four-two-labs/lynx-micro with Docker Model Runner:
```
docker model run hf.co/four-two-labs/lynx-micro
```

alimosavian commited on Jun 7, 2024

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@@ -17,7 +17,7 @@ This is the first release of a series of Swedish large language models we call "
 Lynx micro is a fine-tune of Google DeepMind Gemma 2B, scores just below GPT-3.5 Turbo on [Scandeval](https://scandeval.com/swedish-nlg/). In fact, the only non OpenAI model (currently) topping the Swedish NLG board on scandeval is a fine-tune of Llama-3 by AI Sweden based on our data recipe.
-We believe that this is a really good model (for its size), but keep in mind that it is still a small model and hasn't memorized as much as larger models tend to do.
 - **Funded, Developed and shared by:** [42 Labs](https://www.42labs.ai)

 Lynx micro is a fine-tune of Google DeepMind Gemma 2B, scores just below GPT-3.5 Turbo on [Scandeval](https://scandeval.com/swedish-nlg/). In fact, the only non OpenAI model (currently) topping the Swedish NLG board on scandeval is a fine-tune of Llama-3 by AI Sweden based on our data recipe.
+We believe that this is a really capable model (for its size), but keep in mind that it is still a small model and hasn't memorized as much as larger models tend to do.
 - **Funded, Developed and shared by:** [42 Labs](https://www.42labs.ai)