Instructions to use Sao10K/MN-12B-Lyra-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sao10K/MN-12B-Lyra-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Sao10K/MN-12B-Lyra-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Sao10K/MN-12B-Lyra-v1") model = AutoModelForCausalLM.from_pretrained("Sao10K/MN-12B-Lyra-v1", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Sao10K/MN-12B-Lyra-v1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Sao10K/MN-12B-Lyra-v1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Sao10K/MN-12B-Lyra-v1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Sao10K/MN-12B-Lyra-v1
- SGLang
How to use Sao10K/MN-12B-Lyra-v1 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 "Sao10K/MN-12B-Lyra-v1" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Sao10K/MN-12B-Lyra-v1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "Sao10K/MN-12B-Lyra-v1" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Sao10K/MN-12B-Lyra-v1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Sao10K/MN-12B-Lyra-v1 with Docker Model Runner:
docker model run hf.co/Sao10K/MN-12B-Lyra-v1
EQ Bench Scores
Evaluated on bf16, with both Mistral and ChatML format. Highest one is kept.
Edit: Lyra is nemorun4
My experience kinda reflecting that - feels nice to use, like a sidegrade to nemomix v4. Doesn't feel as smart/ attentive to smaller but key details as nemomix v4 especially if the the information is farther away in the context, but that model's ability too do so feels like a bit of an astounding anomaly. It does feel less censored and writes in a more human way for sure, and less repetitive. The dialogue also feels better - a decent tradeoff! Looking forward to whatever comes next from this too!
Edit: Actually, tested it a bit more and the more I try it the more I like it - it seems like it can actually be pretty smart and recall well, sometimes answer even better than nemomix especially once I toned down the repetition penalty. I guess issue was maybe consistency, but it is already pretty great in its own way, and maybe it's on me for having tried to use the same settings for nemomix v4 as for this model.
