Instructions to use Gryphe/MythoMax-L2-13b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gryphe/MythoMax-L2-13b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Gryphe/MythoMax-L2-13b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Gryphe/MythoMax-L2-13b") model = AutoModelForCausalLM.from_pretrained("Gryphe/MythoMax-L2-13b") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Gryphe/MythoMax-L2-13b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Gryphe/MythoMax-L2-13b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Gryphe/MythoMax-L2-13b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Gryphe/MythoMax-L2-13b
- SGLang
How to use Gryphe/MythoMax-L2-13b 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 "Gryphe/MythoMax-L2-13b" \ --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": "Gryphe/MythoMax-L2-13b", "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 "Gryphe/MythoMax-L2-13b" \ --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": "Gryphe/MythoMax-L2-13b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Gryphe/MythoMax-L2-13b with Docker Model Runner:
docker model run hf.co/Gryphe/MythoMax-L2-13b
'use_cache: false' reduces tokens/sec significantly
I saw a 3x reduction in tokens/sec with cache being disabled,compared to enabled. I don't know why it was disabled, but considering the difference it might be beneficial to have it enabled by default. I used the huggingface loader in text-generation-webui, and ran the model on a 3090.
The config.json file has use_cache: True already set. When I loaded this up in textgen, it stayed set to true. Is there anything special about your setup?
To clarify, I only fixed this yesterday. (I kept forgetting)
Oh! I should have looked at my local copy when I commented, I see that my cache was set to false. Got a nice little speed increase, not 3x, but from 7it/s to 11it/s on a 4090. Thanks metaprotium, wouldn't have known unless you posted. And thanks for the model Gryphe, it's seriously awesome.